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Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 Mignon Marks Principal Author Mignon Marks Project Manager David Ashuckian Manager ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY DIVISION B.B. Blevins Executive Director

2

TRAVEL DEMAND AND RELIABLE FORECASTS  

E-Print Network [OSTI]

TRAVEL DEMAND AND RELIABLE FORECASTS FOR TRANSIT MARK FILIPI, AICP PTP 23rd Annual Transportation transportation projects § Develop and maintain Regional Travel Demand Model § Develop forecast socio in cooperative review during all phases of travel demand forecasting 4 #12;Cooperative Review Should Include

Minnesota, University of

3

Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis  

E-Print Network [OSTI]

Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .

Zhao, Feng

2013-01-01T23:59:59.000Z

4

Forecast Technical Document Forecast Types  

E-Print Network [OSTI]

Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Forecast Types Background Different `types' of forecast are possible for a specified area

5

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 Gorin Principal Authors Lynn Marshall Project Manager Kae C. Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting

6

Distributed Forcing of Forecast and Assimilation Error Systems BRIAN F. FARRELL  

E-Print Network [OSTI]

Distributed Forcing of Forecast and Assimilation Error Systems BRIAN F. FARRELL Division forecast system gov- erning forecast error growth and the tangent linear observer system governing deterministic and stochastic forcings of the forecast and observer systems over a chosen time interval

Farrell, Brian F.

7

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

Stevenson, Paul

8

Solar Forecasting  

Broader source: Energy.gov [DOE]

On December 7, 2012,DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

9

Forecast Technical Document Restocking in the Forecast  

E-Print Network [OSTI]

Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub

10

Mark Johnson  

Broader source: Energy.gov [DOE]

[[{"type":"media","view_mode":"media_large","fid":"799216","attributes":{"alt":"Profile photo of AMO Director Mark Johnson","class":"media-image caption","style":"width: 200px; height: 251px; float...

11

ACCELERATOR DIVISION ANNUAL REPORT, JAN-DEC. 1975  

E-Print Network [OSTI]

F. Voelker H. W. Vogel ACCELERATOR THEORY A. A. Garren L. J.marked a turning point for the Accelerator Division. A majorbright indeed. VII ACCELERATOR DIVISION Contents ACCELERATOR

Lofgren, E.J.

2008-01-01T23:59:59.000Z

12

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS FORECAST IMPROVEMENTS  

E-Print Network [OSTI]

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia and Sunshine Coast. FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 Links

Greenslade, Diana

13

Mark Herrmann  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fund LasDubey selected asMarat Valiev30 MarchARMMarkMarkMark

14

Forecasted Opportunities  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing ZirconiaPolicyFeasibilityFieldMinds" |beamtheFor yourForForecasted

15

Solar forecasting review  

E-Print Network [OSTI]

and forecasting of solar radiation data: a review,forecasting of solar- radiation data, Solar Energy, vol.sequences of global solar radiation data for isolated sites:

Inman, Richard Headen

2012-01-01T23:59:59.000Z

16

2007 National Hurricane Center Forecast Verification Report James L. Franklin  

E-Print Network [OSTI]

storms 17 4. Genesis Forecasts 17 5. Summary and Concluding Remarks 18 a. Atlantic Summary 18 statistical models, provided the best intensity guidance at each time period. The 2007 season marked the first

17

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS  

E-Print Network [OSTI]

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS IMPROVEMENTS FOR QUEENSLAND across Australia From October 2013, new and improved district forecasts will be introduced in Queensland Protection times FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 PTO> Wind

Greenslade, Diana

18

Mark Heer  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fund LasDubey selected asMarat Valiev30 MarchARMMarkMark Heer

19

Using Wikipedia to forecast diseases  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of...

20

Forecast Technical Document Volume Increment  

E-Print Network [OSTI]

Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Division of Finance Division of Finance Alignment  

E-Print Network [OSTI]

Division of Finance Division of Finance Alignment September 11, 2014 1 #12;Division of Finance of Finance Goal of the DF Alignment Project The internal and external alignment of the Division of Finance of Finance The Process We Followed 17 Meetings17 Meetings 120+ Pages of Data 103 Themes 12 Meta Themes Goals

Hayden, Nancy J.

22

ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL  

E-Print Network [OSTI]

5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended

Hamill, Tom

23

Solar forecasting review  

E-Print Network [OSTI]

2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .

Inman, Richard Headen

2012-01-01T23:59:59.000Z

24

Superconducting Magnet Division  

E-Print Network [OSTI]

Superconducting Magnet Division DOE NP Program Review - July 06 1 Brookhaven Magnet Division - Nuclear Physics Program Support Activities Superconducting Magnet Program RHIC Operations Support Spin Summary Peter Wanderer, DOE review, July 25, 2006 Acting Head, Superconducting Magnet Division #12

25

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network [OSTI]

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

26

Technology Forecasting Scenario Development  

E-Print Network [OSTI]

Technology Forecasting and Scenario Development Newsletter No. 2 October 1998 Systems Analysis was initiated on the establishment of a new research programme entitled Technology Forecasting and Scenario and commercial applica- tion of new technology. An international Scientific Advisory Panel has been set up

27

Rainfall-River Forecasting  

E-Print Network [OSTI]

;2Rainfall-River Forecasting Joint Summit II NOAA Integrated Water Forecasting Program · Minimize losses due management and enhance America's coastal assets · Expand information for managing America's Water Resources, Precipitation and Water Quality Observations · USACE Reservoir Operation Information, Streamflow, Snowpack

US Army Corps of Engineers

28

Energy Research and Development Division FINAL PROJECT REPORT  

E-Print Network [OSTI]

Energy Research and Development Division FINAL PROJECT REPORT PROBABILISTIC TRANSMISSION CONGESTION FORECASTING DECEMBER 2012 CEC-500-2013-120 Prepared for: California Energy Commission Prepared by: Electric Research Institute Contract Number: UC MR-052 Prepared for: California Energy Commission Jamie Patterson

29

Energy Research and Development Division FINAL PROJECT REPORT  

E-Print Network [OSTI]

Energy Research and Development Division FINAL PROJECT REPORT EVALUATION OF NUMERICAL WEATHER PREDICTION FOR SOLAR FORECASTING Prepared for: California Energy Commission Prepared by: California Solar Energy Collaborative University of California, San Diego APRIL 2012 CEC-500-2013-115 #12;PRIMARY AUTHOR

30

APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY  

E-Print Network [OSTI]

1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic

Katz, Richard

31

RESEARCH UPDATE Ecology Division  

E-Print Network [OSTI]

1 RESEARCH UPDATE Ecology Division Biotype has changed its name to Ecotype! Following the re-organisation of Forest Research into five science Divisions and three Support Divisions, the former Woodland Ecology Branches to form the new Ecology Division. We decided to give the divisional newsletter a new name (and

32

Markings : design through circumstances  

E-Print Network [OSTI]

This thesis begins as a recording of existing "markings" found on the Massachusetts Cape Cod landscape. The term markings is used throughout to mean: a natural occurrence to the landscape or in human behavior related to ...

Johnson, Heidi

1987-01-01T23:59:59.000Z

33

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network [OSTI]

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

34

Howard S. Marks  

Broader source: Energy.gov [DOE]

Howard Marks is a Program Analyst with the Office of Energy Efficiency and Renewable Energy'sBiomass Program.

35

Method of intrinsic marking  

DOE Patents [OSTI]

A method of pulsed laser intrinsic marking can provide a unique identifier to detect tampering or counterfeiting.

Adams, David P; McDonald, Joel Patrick; Jared, Bradley Howell; Hodges, V. Carter; Hirschfeld, Deidre; Blair, Dianna S

2014-04-01T23:59:59.000Z

36

U.S. Regional Demand Forecasts Using NEMS and GIS  

SciTech Connect (OSTI)

The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-07-01T23:59:59.000Z

37

MORDECAI-MARK MAC LOW CHAIR, DIVISION OF PHYSICAL SCIENCES  

E-Print Network [OSTI]

Glover), $149,912, August 1, 2003 ­ July 31, 2006 National Science Foundation, "CAREER: Structure, and K. Keil (editors), Protostars and Planets V: 63-80. Tucson: University of Arizona Press. Glover, S by gravitational collapse from static initial conditions. Astrophysical Journal Supplement 169: 239-268. Glover, S

38

Probabilistic manpower forecasting  

E-Print Network [OSTI]

PROBABILISTIC MANPOWER FORECASTING A Thesis JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas ASSAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May, 1966 Major Subject...: Computer Science and Statistics PROBABILISTIC MANPOWER FORECASTING A Thesis By JAMES FITZHUGH KOONCE Submitted to the Graduate College of the Texas A@M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE May...

Koonce, James Fitzhugh

1966-01-01T23:59:59.000Z

39

Multivariate Forecast Evaluation And Rationality Testing  

E-Print Network [OSTI]

10621088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): OnKingdom. MULTIVARIATE FORECASTS Kirchgssner, G. , and U. K.2005): Estimation and Testing of Forecast Rationality under

Komunjer, Ivana; OWYANG, MICHAEL

2007-01-01T23:59:59.000Z

40

Division Student Liaisons  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Division Student Liaisons 2014 OFFICE Division Student Liaison Work Email MailStop DIRECTOR'S OFFICE (EA-DO, PCM-DO, CGA-DO, CIO-DO, LC-DO, CFO-DO, HR-OEOD-DO,OMBUDS-DO, LANS,...

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Division of Administration  

E-Print Network [OSTI]

Contracts & Procurement Don Green Controller Steven Yim Budget Planning & Administration Sarah Song Admin Operations Lieutenant Scot Willey Administration Lieutenant John Brockie Division Communication Editorial Communication Editorial Board looks forward to improving communication within and from the Division and welcomes

de Lijser, Peter

42

Division of Agriculture,  

E-Print Network [OSTI]

DAFVM Division of Agriculture, Forestry, and Veterinary M e d i c i n e Visit us online at www to the Mississippi State University Division of Agriculture, Forestry, and Veterinary Medicine. Discrimination based-3-14) Mississippi State University's Division of Agriculture, Forestry, and Veterinary Medicine, or DAFVM

Ray, David

43

DIVISION OF GRADUATE STUDIES  

E-Print Network [OSTI]

recipients at the time of their graduation to monitor and project the scientific workforce. Between 1961DIVISION OF GRADUATE STUDIES 2012-2013 ACADEMIC YEAR REpORT Excellence in Action Division of Graduate Studies #12;Division of Graduate Studies Kent State University 2012 - 2013 Academic Year Report

Palffy-Muhoray, Peter

44

3, 21452173, 2006 Probabilistic forecast  

E-Print Network [OSTI]

HESSD 3, 2145­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC ­ Department­2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction

Paris-Sud XI, Université de

45

4, 189212, 2007 Forecast and  

E-Print Network [OSTI]

OSD 4, 189­212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction

Paris-Sud XI, Université de

46

Forecast Technical Document Technical Glossary  

E-Print Network [OSTI]

Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others

47

Forecast Technical Document Tree Species  

E-Print Network [OSTI]

Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 ­ List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically

48

Consensus Coal Production Forecast for  

E-Print Network [OSTI]

in the consensus forecast produced in 2006, primarily from the decreased demand as a result of the current nationalConsensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks

Mohaghegh, Shahab

49

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

50

Demand Forecasting of New Products  

E-Print Network [OSTI]

Demand Forecasting of New Products Using Attribute Analysis Marina Kang A thesis submitted Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock upon currently employed new-SKU demand forecasting methods which involve the processing of large

Sun, Yu

51

Improving Inventory Control Using Forecasting  

E-Print Network [OSTI]

EMGT 835 FIELD PROJECT: Improving Inventory Control Using Forecasting By Juan Mario Balandran jmbg@hotmail.com Master of Science The University of Kansas Fall Semester, 2005 An EMGT Field Project report submitted...............................................................................................................................................10 Current Inventory Forecast Process ...........................................................................................10 Development of Alternative Forecast Process...

Balandran, Juan

2005-12-16T23:59:59.000Z

52

Fuel Price Forecasts INTRODUCTION  

E-Print Network [OSTI]

Fuel Price Forecasts INTRODUCTION Fuel prices affect electricity planning in two primary ways and water heating, and other end-uses as well. Fuel prices also influence electricity supply and price because oil, coal, and natural gas are potential fuels for electricity generation. Natural gas

53

Solar forecasting review  

E-Print Network [OSTI]

Quantifying PV power output variability, Solar Energy, vol.each solar sen at node i, P(t) the total power output of theSolar Forecasting Historically, traditional power generation technologies such as fossil and nu- clear power which were designed to run in stable output

Inman, Richard Headen

2012-01-01T23:59:59.000Z

54

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Edition, Editors:Forecasting and Resource Assessment, 1 st Ed.. Editor: Jan

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

55

Engineering Division Superconducting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

& Engineering Division Superconducting Magnet Technology for Fusion and Large Scale Applications Joseph V. Minervini Massachusetts Institute of Technology Plasma Science and Fusion...

56

Forecasting oilfield economic performance  

SciTech Connect (OSTI)

This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended.

Bradley, M.E. (Univ. of Chicago, IL (United States)); Wood, A.R.O. (BP Exploration, Anchorage, AK (United States))

1994-11-01T23:59:59.000Z

57

Hypertension Research Division  

E-Print Network [OSTI]

Hypertension & Vascular Research Division Department of Internal Medicine Jeffrey L. Garvin, Ph.D. ­ Division Head #12;Prevalence of Hypertension in U.S. Men by Age and Ethnicity 18 ­ 29 30 ­ 39 40 ­ 49 50 Prevalence of High BP Adapted from Burt et al. Hypertension 1995;25:305. 25 50 75 #12;Introduction

Berdichevsky, Victor

58

Superconducting Magnet Division  

E-Print Network [OSTI]

Superconducting Magnet Division Ramesh Gupta 20T Target Solenoid with HTS Insert Solenoid Capture Laboratory New York, USA http://www.bnl.gov/magnets/staff/gupta #12;Superconducting Magnet Division Ramesh of HTS may significantly reduce the amount of Tungsten shielding · Summary #12;Superconducting Magnet

McDonald, Kirk

59

Forecast Technical Document Growing Stock Volume  

E-Print Network [OSTI]

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

60

DIVISION & TECHNICAL COMMITTEE MEMBERSHIP: -Division Chair of the ASME NDE (Nondestructive Evaluation) Division, 2003-2005  

E-Print Network [OSTI]

DIVISION & TECHNICAL COMMITTEE MEMBERSHIP: - Division Chair of the ASME NDE (Nondestructive Evaluation) Division, 2003-2005 - Member of the Executive Committee of the ASME NDE Engineering Division, 1997-present - Secretary and Vice-Chairman of the ASME NDE Division from 2001 to 2003 - Program

Wong, Pak Kin

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

NOAA Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps  

E-Print Network [OSTI]

Forecast System Southwest Florida Forecast Region Maps 0 20 4010 Miles #12;Bay-S Pinellas Bay-UPR Bay Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12;Bay Harmful Algal Bloom Operational Forecast System Southwest Florida Forecast Region Maps 0 5 102.5 Miles #12

62

Price forecasting for notebook computers.  

E-Print Network [OSTI]

??This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a (more)

Rutherford, Derek Paul

2012-01-01T23:59:59.000Z

63

UWIG Forecasting Workshop -- Albany (Presentation)  

SciTech Connect (OSTI)

This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

Lew, D.

2011-04-01T23:59:59.000Z

64

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network [OSTI]

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL

65

Conservation The Northwest ForecastThe Northwest Forecast  

E-Print Network [OSTI]

& Resources Creating Mr. Toad's Wild Ride for the PNW's Energy Efficiency InCreating Mr. Toad's Wild RideNorthwest Power and Conservation Council The Northwest ForecastThe Northwest Forecast Energy EfficiencyEnergy Efficiency Dominates ResourceDominates Resource DevelopmentDevelopment Tom EckmanTom Eckman

66

NATIONAL AND GLOBAL FORECASTS WEST VIRGINIA PROFILES AND FORECASTS  

E-Print Network [OSTI]

· NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Research West Virginia University College of Business and Economics P.O. Box 6527, Morgantown, WV 26506 EXPERT OPINION PROVIDED BY Keith Burdette Cabinet Secretary West Virginia Department of Commerce

Mohaghegh, Shahab

67

CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST  

E-Print Network [OSTI]

1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find

Paris-Sud XI, Université de

68

STAFF FORECAST OF 2007 PEAK STAFFREPORT  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2.............................................................................................. 10 #12;Introduction and Background This document describes staff's updated 2007 peak demand forecasts

69

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product estimates. Margaret Sheridan provided the residential forecast. Mitch Tian prepared the peak demand

70

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

71

2009 CAPS Spring Forecast Program Plan  

E-Print Network [OSTI]

package. · Two 18 UTC update forecasts on demand basis, with the same domain and configuration, running2009 CAPS Spring Forecast Experiment Program Plan April 20, 2009 #12;2 Table of Content 1. Overview .......................................................................................................4 3. Forecast System Configuration

Droegemeier, Kelvin K.

72

Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast  

E-Print Network [OSTI]

Forecast Introduction.................................................................................................................................... 6 Demand................................................................... 16 The Base Case Forecast

73

Electricity price forecasting in a grid environment.  

E-Print Network [OSTI]

??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate (more)

Li, Guang, 1974-

2007-01-01T23:59:59.000Z

74

Regional-seasonal weather forecasting  

SciTech Connect (OSTI)

In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

1980-08-01T23:59:59.000Z

75

Division Student Liaisons  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

None Fire Protection (FP-DO) Robert J. Farris (Rob) 667-9045 sirraf@lanl.gov K493 Nuclear Criticality Safety None Operations Support Division (OS-DO) None Radiological...

76

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast uncertainty  

E-Print Network [OSTI]

Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast structures Stochastic trajectory Stochastic FTLE field Ensemble forecasting Uncertainty analysis a b s t r of the forecast FTLE fields is analyzed using ensemble forecasting. Unavoidable errors of the forecast velocity

Ross, Shane

77

Mark Bowden | EMSL  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartment MariusMark

78

ZYGO Mark Ivxp Interferometer  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste andAnniversary, part 2 ContinuingYanYoussefYue LuZYGO Mark Ivxp

79

Adaptation of Fuzzy Inferencing: A Survey Payman Arabshahi, Robert J. Marks II, and Russell Reed  

E-Print Network [OSTI]

by input membership functions and processed by a fuzzy logic interpretation of a set of fuzzy rules Control Forecasting Estimation Figure 1: Block diagram of a general fuzzy inference system: The errorAdaptation of Fuzzy Inferencing: A Survey Payman Arabshahi, Robert J. Marks II, and Russell Reed

Arabshahi, Payman

80

PROBLEMS OF FORECAST1 Dmitry KUCHARAVY  

E-Print Network [OSTI]

1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY dmitry.kucharavy@insa-strasbourg.fr Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
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We encourage you to perform a real-time search of NLEBeta
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81

Using reforecasts for probabilistic forecast calibration  

E-Print Network [OSTI]

1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating

Hamill, Tom

82

Forecast Combination With Outlier Protection Gang Chenga,  

E-Print Network [OSTI]

Forecast Combination With Outlier Protection Gang Chenga, , Yuhong Yanga,1 a313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455 Abstract Numerous forecast combination schemes with distinct on combining forecasts with minimizing the occurrence of forecast outliers in mind. An unnoticed phenomenon

Yuhong, Yang

83

Forecast Technical Document Felling and Removals  

E-Print Network [OSTI]

Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Felling and removals forecasts Background A fellings and removals

84

Assessing Forecast Accuracy Measures Department of Economics  

E-Print Network [OSTI]

Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form

85

Load Forecast For use in Resource Adequacy  

E-Print Network [OSTI]

-term Electricity Demand Forecasting System 1) Obtain Daily Regional Temperatures 6) Estimate Daily WeatherLoad Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l­ Load forecast methodology ­ Drivers of the forecast f i­ Treatment of conservation

86

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

87

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network [OSTI]

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

88

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network [OSTI]

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work Sheridan provided the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid

89

Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model  

E-Print Network [OSTI]

1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates

90

Can earnings forecasts be improved by taking into account the forecast bias?  

E-Print Network [OSTI]

Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi

Paris-Sud XI, Université de

91

Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts  

E-Print Network [OSTI]

Revised Economic andRevised Economic and Demand ForecastsDemand Forecasts April 14, 2009 Massoud,000 MW #12;6 Demand Forecasts Price Effect (prior to conservation) - 5,000 10,000 15,000 20,000 25,000 30 Jourabchi #12;2 Changes since the Last Draft ForecastChanges since the Last Draft Forecast Improved

92

Price forecasting for notebook computers  

E-Print Network [OSTI]

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence...

Rutherford, Derek Paul

2012-06-07T23:59:59.000Z

93

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network [OSTI]

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN with primary contributions in the area of decision support for reservoir planning and management Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project

94

Arnold Schwarzenegger INTEGRATED FORECAST AND  

E-Print Network [OSTI]

Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN: California Energy Commission Energy-Related Environmental Research Joseph O' Hagan Contract Manager Joseph O' Hagan Project Manager Kelly Birkinshaw Program Area Manager ENERGY-RELATED ENVIRONMENTAL RESEARCH Martha

95

Value of Wind Power Forecasting  

SciTech Connect (OSTI)

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01T23:59:59.000Z

96

CALIFORNIA ENERGY COMMISSION0 Annual Update to the Forecasted  

E-Print Network [OSTI]

Values in TWh forthe Year2022 Formula Mid Demand Forecast Renewable Net High Demand Forecast Renewable Net Low Demand Forecast Renewable Net #12;CALIFORNIA ENERGY COMMISSION5 Demand Forecast · Retail Sales Forecast from California Energy Demand 2012 2022(CED 2011), Adopted Forecast* ­ Form 1.1c · Demand Forecast

97

Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting  

E-Print Network [OSTI]

This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...

Goto, Susumu

2007-01-01T23:59:59.000Z

98

Solid State Division  

SciTech Connect (OSTI)

This report contains brief discussions on work done in the Solid State Division of Oak Ridge National Laboratory. The topics covered are: Theoretical Solid State Physics; Neutron scattering; Physical properties of materials; The synthesis and characterization of materials; Ion beam and laser processing; and Structure of solids and surfaces. (LSP)

Green, P.H.; Watson, D.M. (eds.)

1989-08-01T23:59:59.000Z

99

Superconducting Magnet Division  

E-Print Network [OSTI]

Superconducting Magnet Division MAGNETIC DESIGN OF E-LENS SOLENOID AND CORRECTOR SYSTEM FOR RHIC* R Slotted Dipole Corrector Design · Slots are machined in an Al tube where superconducting wires are placed between superconducting and copper solenoid with superconducting solenoid at 6T · The desired field (>0

Ohta, Shigemi

100

Wind Forecast Improvement Project Southern Study Area Final Report...  

Office of Environmental Management (EM)

Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern...

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

102

Applying Bayesian Forecasting to Predict New Customers' Heating Oil Demand.  

E-Print Network [OSTI]

??This thesis presents a new forecasting technique that estimates energy demand by applying a Bayesian approach to forecasting. We introduce our Bayesian Heating Oil Forecaster (more)

Sakauchi, Tsuginosuke

2011-01-01T23:59:59.000Z

103

Chemistry Division Department of Biological  

E-Print Network [OSTI]

1 Chemistry Division Department of Biological and Chemical Sciences, Illinois Institute-13 Chemistry Division invites nominations for Kilpatrick Fellowship for the academic year 2012's Chemistry Department from 1947­1960. Mary Kilpatrick was a chemistry faculty member from 1947

Heller, Barbara

104

Mark Jankowski: Minnesota Pollution Control Agency  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Mark Jankowski: Minnesota Pollution Control Agency March 1, 2015 Mark Jankowski now at Minnesota Pollution Control Agency - 2 - Mark Jankowski worked at the Lab twice: first after...

105

Environment, Health & Safety Division 31 July, 2009  

E-Print Network [OSTI]

Environment, Health & Safety Division 31 July, 2009 MEMORANDUM To: Division Safety Coordinators Division Liaisons All JHA Users From: John Seabury Environment, Health & Safety Division Subject: Job Hazard Analysis ­ Description of Work Rev 5 Discussion, Requirements, Helpful Hints and Examples

106

Computer, Computational, and Statistical Sciences Division  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Computing CCS Division Computer, Computational, and Statistical Sciences Division Computational physics, computer science, applied mathematics, statistics and the integration of...

107

Mark Walker Director of Public Affairs  

E-Print Network [OSTI]

to a significant extent by oil prices, and the U.S. Energy Information Administration's oil supply forecasts countries. The authors of the report acknowledge on page 14, that retail price forecasts of world oil are based on simple historical relationships between wholesale oil prices and retail prices. Forecasting

108

Aggregate vehicle travel forecasting model  

SciTech Connect (OSTI)

This report describes a model for forecasting total US highway travel by all vehicle types, and its implementation in the form of a personal computer program. The model comprises a short-run, econometrically-based module for forecasting through the year 2000, as well as a structural, scenario-based longer term module for forecasting through 2030. The short-term module is driven primarily by economic variables. It includes a detailed vehicle stock model and permits the estimation of fuel use as well as vehicle travel. The longer-tenn module depends on demographic factors to a greater extent, but also on trends in key parameters such as vehicle load factors, and the dematerialization of GNP. Both passenger and freight vehicle movements are accounted for in both modules. The model has been implemented as a compiled program in the Fox-Pro database management system operating in the Windows environment.

Greene, D.L.; Chin, Shih-Miao; Gibson, R. [Tennessee Univ., Knoxville, TN (United States)

1995-05-01T23:59:59.000Z

109

Management forecast credibility and underreaction to news  

E-Print Network [OSTI]

In this paper, we first document evidence of underreaction to management forecast news. We then hypothesize that the credibility of the forecast influences the magnitude of this underreaction. Relying on evidence that more ...

Ng, Jeffrey

110

Management Forecast Quality and Capital Investment Decisions  

E-Print Network [OSTI]

Corporate investment decisions require managers to forecast expected future cash flows from potential investments. Although these forecasts are a critical component of successful investing, they are not directly observable ...

Goodman, Theodore H.

111

FORECASTING THE ROLE OF RENEWABLES IN HAWAII  

E-Print Network [OSTI]

FORECASTING THE ROLE OF RENEWABLES IN HAWAII Jayant SathayeFORECASTING THE ROLF OF RENEWABLES IN HAWAII J Sa and Henrythe Conservation Role of Renewables November 18, 1980 Page 2

Sathaye, Jayant

2013-01-01T23:59:59.000Z

112

Improving week two forecasts with multi-model re-forecast ensembles  

E-Print Network [OSTI]

Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr´ed´eric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill

Whitaker, Jeffrey S.

113

Invasion Biology Mark A. Davis  

E-Print Network [OSTI]

Invasion Biology Mark A. Davis 2 biology 2 MarkA.DavisInvasionBiology2 1 With the exception of climate change, biological invasions have probably received more attention during the past ten years than on the subject, Invasion Biology provides a comprehensive and up-to-date review of the science of biological

Davis, Mark A.

114

5, 183218, 2008 A rainfall forecast  

E-Print Network [OSTI]

HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183­218, 2008 A rainfall forecast model using Artificial Neural Network N

Paris-Sud XI, Université de

115

Ensemble Forecast of Analyses With Uncertainty Estimation  

E-Print Network [OSTI]

Ensemble Forecast of Analyses With Uncertainty Estimation Vivien Mallet1,2, Gilles Stoltz3 2012 Mallet, Stoltz, Zhuk, Nakonechniy Ensemble Forecast of Analyses November 2012 1 / 14 hal-00947755,version1-21Feb2014 #12;Objective To produce the best forecast of a model state using a data assimilation

Boyer, Edmond

116

(1) Ensemble forecast calibration & (2) using reforecasts  

E-Print Network [OSTI]

1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast ­ Rationale 1: Infer large-sample probabilities from small ensemble. ­ Rationale 2: Remove bias, increase forecast reliability while preserving

Hamill, Tom

117

Load forecast and treatment of conservation  

E-Print Network [OSTI]

conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservationLoad forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee in the short-term model Our short-term model is an econometric model which can not explicitly forecast

118

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the peak demand forecast. Ravinderpal Vaid provided the projections of commercial floor space

119

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

120

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy for demand response program impacts and contributed to the residential forecast. Mitch Tian prepared

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

122

Consensus Coal Production And Price Forecast For  

E-Print Network [OSTI]

Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast

Mohaghegh, Shahab

123

Load Forecasting of Supermarket Refrigeration  

E-Print Network [OSTI]

energy system. Observed refrigeration load and local ambient temperature from a Danish su- permarket renewable energy, is increasing, therefore a flexible energy system is needed. In the present ThesisLoad Forecasting of Supermarket Refrigeration Lisa Buth Rasmussen Kongens Lyngby 2013 M.Sc.-2013

124

Division Student Liaisons  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation Proposed Newcatalyst phasesDataTranslocationDiurnal Cycle of Convection atDiversityDivision

125

Engineering Division Superconducting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing Zirconia NanoparticlesSmart GrocerDepartment& Engineering Division

126

Mark Reeves Associate Director, Commercialization  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartmentMarkMarkMark

127

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the

128

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark

129

Forecasting Distributions with Experts Advice  

E-Print Network [OSTI]

) is the probability forecast based on an arbitrary vector wE in the unit simplex, experts forecasts ?E , and model {p?} . Remark 2 In most cases, we can choose c = 1/?, implying in the result below that c? = 1. Example 3 The prediction function is a mixture... 0 = 1, and #IT (k) = tk+1 ? tk. Define ek ? E. Theorem 12 Under Conditions 1 and 7, R1,...,t (pW ) ? c? K? k=0 Rt(k),...,t(k+1)?1 ( p?(e(k)) ) + c ln (#E) ?c K? k=1 ln ut(k) (ek, ek?1)? c K? k=0 t(k+1)?2? s=t(k) ln (us+1 (ek, ek)) . 9 Remark 13...

Sancetta, Alessio

2006-03-14T23:59:59.000Z

130

Forecasting wind speed financial return  

E-Print Network [OSTI]

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

131

Systems Division NO. REV. NO.  

E-Print Network [OSTI]

Aerospace Systems Division NO. REV. NO. EATM-17 PCU - SOLAR PANEL SIMULATOR TEST REPORT:' Courtois ~ll~K. Hsi #12;MO. REV. MO. EATM-17 ~ Systems Division PCU - Solar Panel Simulator Test Report Conditioning Unit (PCU) is compatible with a solar panel array. The Solar Panel Simulator and the PCU Test Set

Rathbun, Julie A.

132

Superconducting Magnet Division Mike Harrison  

E-Print Network [OSTI]

Superconducting Magnet Division Mike Harrison The LARP Dipole R&D Program - D1 only Design (high beta lattice location) · Beam heating (first active element from the IP) #12;Superconducting aperture Field quality Issues not (well ?) understood #12;Superconducting Magnet Division Mike Harrison

Large Hadron Collider Program

133

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating Solar Power Basics (TheEtelligence (SmartHome Kyoung's pictureFlintFlowerForecast

134

Genomics Division Home  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsingFun with Big Sky Learning Fun withGenepoolCrystals.Genomefor Genomics DanPIs Mark

135

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of Friday October 22 and

136

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of Friday October 22

137

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of Friday October

138

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of Friday

139

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of Friday

140

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of FridayRadioactive

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates of

142

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOS Proposal

143

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOS ProposalThe

144

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOS

145

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSThe ATLAS Program

146

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSThe ATLAS

147

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSThe

148

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSTheGeneral Safety

149

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSTheGeneral

150

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSTheGeneralCARIBU

151

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates ofHELIOSTheGeneralCARIBU2

152

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the dates

153

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the datesScheduling Considerations

154

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the datesScheduling

155

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the datesSchedulingATLAS Data

156

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark the datesSchedulingATLAS

157

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining Requirements for ATLAS

158

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining Requirements for

159

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining Requirements forGuest

160

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining Requirements

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining RequirementsProposed

162

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTraining

163

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTrainingEquipment Initiatives at

164

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTrainingEquipment Initiatives

165

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTrainingEquipment

166

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTrainingEquipmentCARIBU Beam

167

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, mark theTrainingEquipmentCARIBU

168

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name: First Middle

169

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name: First

170

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name: First2014

171

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name:

172

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name:2014 ATLAS

173

Argonne Physics Division - ATLAS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-Series to someone byDear Friend, Please, markREGISTRATION FORM Name:2014

174

Materials Science & Tech Division | Advanced Materials | ORNL  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Materials Science and Technology SHARE Materials Science and Technology Division The Materials Science and Technology Division is unique within the Department of Energy (DOE)...

175

ENERGY & ENVIRONMENT DIVISION ANNUAL REPORT 1979  

E-Print Network [OSTI]

Population Impacts of Geothermal Energy Development in thethe DOE Division of Geothermal Energy. S. L. Phillips and E.to DOE Division of Geothermal Energy, January 30, 1980.

Cairns, E.J.

2010-01-01T23:59:59.000Z

176

EARTH SCIENCES DIVISION ANNUAL REPORT 1978  

E-Print Network [OSTI]

of Energy's Division of Geothermal Energy has undertaken aand Ghormley, E. L. , 1976. Geothermal energy conversion andof the Division of Geothermal Energy, and is compatible with

Authors, Various

2012-01-01T23:59:59.000Z

177

Mark Nutt | Argonne National Laboratory  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartmentMarkMark Nutt

178

Mark Peters | Argonne National Laboratory  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartmentMarkMark

179

Geothermal wells: a forecast of drilling activity  

SciTech Connect (OSTI)

Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.

Brown, G.L.; Mansure, A.J.; Miewald, J.N.

1981-07-01T23:59:59.000Z

180

Online Forecast Combination for Dependent Heterogeneous Data  

E-Print Network [OSTI]

the single individual forecasts. Several studies have shown that combining forecasts can be a useful hedge against structural breaks, and forecast combinations are often more stable than single forecasts (e.g. Hendry and Clements, 2004, Stock and Watson, 2004... in expectations. Hence, we have the following. Corollary 4 Suppose maxt?T kl (Yt, hwt,Xti)kr ? A taking expectation on the left hand side, adding 2A ? T and setting ? = 0 in mT (?), i.e. TX t=1 E [lt (wt)? lt (ut...

Sancetta, Alessio

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Funding Opportunity Announcement for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

182

Upcoming Funding Opportunity for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

183

Solid low-level waste forecasting guide  

SciTech Connect (OSTI)

Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford`s experience within the last six years. Hanford`s forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford`s annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford`s forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data.

Templeton, K.J.; Dirks, L.L.

1995-03-01T23:59:59.000Z

184

The Value of Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

185

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network [OSTI]

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud://www.dis.anl.gov/projects/windpowerforecasting.html IAWind 2010 Ames, IA, April 6, 2010 #12;Outline Background Using wind power forecasts in market operations ­ Current status in U.S. markets ­ Handling uncertainties in system operations ­ Wind power

Kemner, Ken

186

U-M Construction Forecast December 15, 2011 U-M Construction Forecast  

E-Print Network [OSTI]

U-M Construction Forecast December 15, 2011 U-M Construction Forecast Spring Fall 2012 As of December 15, 2011 Prepared by AEC Preliminary & Advisory #12;U-M Construction Forecast December 15, 2011 Overview Campus by campus Snapshot in time Not all projects Construction coordination efforts

Kamat, Vineet R.

187

NOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future)  

E-Print Network [OSTI]

conditions for up to 5 days in the future. These forecasts are run twice daily, and you can step through are generated every 6 hours and you can step backward in hourly increments to view conditions over the previousNOAA GREAT LAKES COASTAL FORECASTING SYSTEM Forecasts (up to 5 days in the future) and Nowcasts

188

Physics division annual report 2006.  

SciTech Connect (OSTI)

This report highlights the activities of the Physics Division of Argonne National Laboratory in 2006. The Division's programs include the operation as a national user facility of ATLAS, the Argonne Tandem Linear Accelerator System, research in nuclear structure and reactions, nuclear astrophysics, nuclear theory, investigations in medium-energy nuclear physics as well as research and development in accelerator technology. The mission of nuclear physics is to understand the origin, evolution and structure of baryonic matter in the universe--the core of matter, the fuel of stars, and the basic constituent of life itself. The Division's research focuses on innovative new ways to address this mission.

Glover, J.; Physics

2008-02-28T23:59:59.000Z

189

Physics Division computer facilities  

SciTech Connect (OSTI)

The Physics Division maintains several computer systems for data analysis, general-purpose computing, and word processing. While the VMS VAX clusters are still used, this past year saw a greater shift to the Unix Cluster with the addition of more RISC-based Unix workstations. The main Divisional VAX cluster which consists of two VAX 3300s configured as a dual-host system serves as boot nodes and disk servers to seven other satellite nodes consisting of two VAXstation 3200s, three VAXstation 3100 machines, a VAX-11/750, and a MicroVAX II. There are three 6250/1600 bpi 9-track tape drives, six 8-mm tapes and about 9.1 GB of disk storage served to the cluster by the various satellites. Also, two of the satellites (the MicroVAX and VAX-11/750) have DAPHNE front-end interfaces for data acquisition. Since the tape drives are accessible cluster-wide via a software package, they are, in addition to replay, used for tape-to-tape copies. There is however, a satellite node outfitted with two 8 mm drives available for this purpose. Although not part of the main cluster, a DEC 3000 Alpha machine obtained for data acquisition is also available for data replay. In one case, users reported a performance increase by a factor of 10 when using this machine.

Cyborski, D.R.; Teh, K.M.

1995-08-01T23:59:59.000Z

190

Environmental & Waste Management Services Division Bldg. 120 P. O. Box 5000  

E-Print Network [OSTI]

Environmental & Waste Management Services Division Bldg. 120 P. O. Box 5000 Upton, NY 11973.S. Department of Energy MMeemmooDate: August 5, 2008 To: N. Gmur From: Mark C. Davis, NEPA/NHPA Coordinator Synchrotron Light Source-II (NSLS-II) Environmental Assessment (EA) Vs Title II Design Specifications, dated 6

Ohta, Shigemi

191

Mark W. Grinstaff Boston University  

E-Print Network [OSTI]

1 Mark W. Grinstaff Boston University Departments of Biomedical Engineering and Chemistry Metcalf of Biomedical Engineering, College of Engineering, Boston University, Boston, MA. 2009 - Professor of Chemistry Center for Science and Engineering 590 Commonwealth Avenue, Boston, MA 02215 Tel: 617.358.3429, Fax: 617

192

Mark Kaplan Department of Philosophy  

E-Print Network [OSTI]

Mark Kaplan Professor Department of Philosophy Indiana University Tel: 812.855.2539 (office) E-mail: kaplanm@indiana.edu Education 1978, Ph.D. The University of Michigan (philosophy) 1976, A.M. The University of Michigan (philosophy) 1973, A.B. Brown University (honors in philosophy) Employment Since 2002

Indiana University

193

Optimal combined wind power forecasts using exogeneous variables  

E-Print Network [OSTI]

Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

194

Ensemble forecast of analyses: Coupling data assimilation and sequential aggregation  

E-Print Network [OSTI]

Ensemble forecast of analyses: Coupling data assimilation and sequential aggregation Vivien Mallet1. [1] Sequential aggregation is an ensemble forecasting approach that weights each ensemble member based on past observations and past forecasts. This approach has several limitations: The weights

Mallet, Vivien

195

Probabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging  

E-Print Network [OSTI]

is to issue deterministic forecasts based on numerical weather prediction models. Uncertainty canProbabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging J. Mc discretization than is seen in other weather quantities. The prevailing paradigm in weather forecasting

Washington at Seattle, University of

196

Coordinating production quantities and demand forecasts through penalty schemes  

E-Print Network [OSTI]

Coordinating production quantities and demand forecasts through penalty schemes MURUVVET CELIKBAS1 departments which enable organizations to match demand forecasts with production quantities. This research problem where demand is uncertain and the marketing de- partment provides a forecast to manufacturing

Swaminathan, Jayashankar M.

197

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy-2 Demand Forecast Disaggregation......................................................1-4 Statewide

198

HIERARCHY OF PRODUCTION DECISIONS Forecasts of future demand  

E-Print Network [OSTI]

HIERARCHY OF PRODUCTION DECISIONS Forecasts of future demand Aggregate plan Master production Planning and Forecast Bias · Forecast error seldom is normally distributed · There are few finite planning

Brock, David

199

Forecasting Market Demand for New Telecommunications Services: An Introduction  

E-Print Network [OSTI]

Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

Parsons, Simon

200

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network [OSTI]

has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

NREL: Transmission Grid Integration - Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and ResourcesOtherForecasting NREL researchers use solar and

202

DIVISION 16 -ELECTRICAL 16000 GENERAL  

E-Print Network [OSTI]

Electrical Code American National Standards Institute National Electrical Manufacturers Association Institute of Electrical & Electronics Engineers Insulated Cable Engineers Association 3. Three copies of the followingDIVISION 16 - ELECTRICAL _____________________________________________________________ 16000

203

Division 1137 property control system  

SciTech Connect (OSTI)

An automated data processing property control system was developed by Mobile and Remote Range Division 1137. This report describes the operation of the system and examines ways of using it in operational planning and control.

Pastor, D.J.

1982-01-01T23:59:59.000Z

204

Lawrence Berkeley National Laboratory Engineering Division Office  

E-Print Network [OSTI]

/4867399 DMAttia@lbl.gov Administrative Staff Glenda Fish Division Office Administrator 510/4867123 GJFish

205

Nuclear Engineering Division Think, explore, discover, innovate  

E-Print Network [OSTI]

Nuclear Engineering Division Think, explore, discover, innovate Never miss important updates managed by UChicago Argonne, LLC 1 Nuclear Engineering Division: Awards Listing (1980 ­ present) Web: http Division of Educational Programs J.C. Braun L.W. Deitrich #12;Nuclear Engineering Division Think, explore

Kemner, Ken

206

The Wind Forecast Improvement Project (WFIP): A Public/Private...  

Energy Savers [EERE]

The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

207

Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo  

E-Print Network [OSTI]

Forecasting of Solar Radiation Detlev Heinemann, Elke Lorenz, Marco Girodo Oldenburg University have been presented more than twenty years ago (Jensenius, 1981), when daily solar radiation forecasts

Heinemann, Detlev

208

New Concepts in Wind Power Forecasting Models  

E-Print Network [OSTI]

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

209

Inverse Modelling to Forecast Enclosure Fire Dynamics  

E-Print Network [OSTI]

. This thesis proposes and studies a method to use measurements of the real event in order to steer and accelerate fire simulations. This technology aims at providing forecasts of the fire development with a positive lead time, i.e. the forecast of future events...

Jahn, Wolfram

210

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near-surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

211

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near­surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

212

Nonparametric models for electricity load forecasting  

E-Print Network [OSTI]

Electricity consumption is constantly evolving due to changes in people habits, technological innovations1 Nonparametric models for electricity load forecasting JANUARY 23, 2015 Yannig Goude, Vincent at University Paris-Sud 11 Orsay. His research interests are electricity load forecasting, more generally time

Genève, Université de

213

UHERO FORECAST PROJECT DECEMBER 5, 2014  

E-Print Network [OSTI]

deficits. After solid 3% growth this year, real GDP growth will recede a bit for the next two years. New household spending. Real GDP will firm above 3% in 2015. · The pace of growth in China has continuedUHERO FORECAST PROJECT DECEMBER 5, 2014 Asia-Pacific Forecast: Press Version: Embargoed Until 2

214

-Assessment of current water conditions -Precipitation Forecast  

E-Print Network [OSTI]

#12;-Assessment of current water conditions - Precipitation Forecast - Recommendations for Drought of the mountains, so early demand for irrigation water should be minimal as we officially move into spring. Western, it is forecast to bring wet snow to the eastern slope of the Rockies, with less accumulations west of the divide

215

A NEW APPROACH FOR EVALUATING ECONOMIC FORECASTS  

E-Print Network [OSTI]

APPROACH FOR EVALUATING ECONOMIC FORECASTS Tara M. Sinclair , H.O. Stekler, and Warren Carnow Department of Economics The George Washington University Monroe Hall #340 2115 G Street NW Washington, DC 20052 JEL Codes, Mahalanobis Distance Abstract This paper presents a new approach to evaluating multiple economic forecasts

Vertes, Akos

216

2013 Midyear Economic Forecast Sponsorship Opportunity  

E-Print Network [OSTI]

2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, ­ Hyatt Regency Irvine 11:30 a.m. ­ 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing and Economics at California State University, Fullerton, the largest accredited business school in California

de Lijser, Peter

217

1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.  

SciTech Connect (OSTI)

This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

United States. Bonneville Power Administration.

1994-02-01T23:59:59.000Z

218

Earthquake Forecast via Neutrino Tomography  

E-Print Network [OSTI]

We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \

Bin Wang; Ya-Zheng Chen; Xue-Qian Li

2011-03-29T23:59:59.000Z

219

Physics Division progress report for period ending September 30, 1988  

SciTech Connect (OSTI)

This report covers the research and development activities of the Physics Division for the 1988 fiscal year, beginning October 1, 1987, and ending September 30, 1988. The activities of this Division are concentrated in the areas of experimental nuclear physics, experimental atomic physics, and theoretical nuclear and atomic physics. Operation of the Holifield Heavy Ion Research Facility as a national user facility continues to represent the single largest activity within the Division. This year saw the completion of the acceleration tube upgrade of the 25-MV tandem electrostatic accelerator and the achievement of record terminal potentials, operation for an experiment with 25 million volts on terminal, and successful tests with beam at 25.5 MV. The experimental nuclear physics program continues to be dominated by research utilizing heavy ions. These activities, while continuing to center largely on the Holifield Facility, have seen significant growth in the use of facilities that provide intermediate energies and especially ultrarelativistic beams. The UNISOR program, since its inception, has been intimately associated with the Division and, most particularly, with the Holifield Facility. In addition to the Holifield Facility, the Division operates two smaller facilities, the EN Tandem and the ECR Ion Source Facility, as ''User Resources.'' The efforts in theoretical physics, covering both nuclear and atomic physics, are presented. In addition to research with multicharged heavy ions from the ECR source, the effort on atomic physics in support of the controlled fusion program includes a plasma diagnostics development program. The concentration of this program on optical and laser technology is marked by the change in designation to the Laser and Electro-Optics Lab. A small, continuing effort in elementary particle physics, carried out in collaboration with the University of Tennessee, is reported.

Livingston, A.B. (ed.)

1989-03-01T23:59:59.000Z

220

MSSM Forecast for the LHC  

E-Print Network [OSTI]

We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered, the preferred region (for $\\mu>0$) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-$\\mu$ possibilities.

Maria Eugenia Cabrera; Alberto Casas; Roberto Ruiz de Austri

2010-12-10T23:59:59.000Z

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221

1993 Solid Waste Reference Forecast Summary  

SciTech Connect (OSTI)

This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.

Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)

1993-08-01T23:59:59.000Z

222

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

223

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng  

E-Print Network [OSTI]

A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations

Kim, Kiho

224

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT  

E-Print Network [OSTI]

AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT OF USING FORECASTS Mohamed Zied Ch^atenay-Malabry Cedex, France Abstract: In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given

Paris-Sud XI, Université de

225

The Complexity of Forecast Testing Lance Fortnow # Rakesh V. Vohra +  

E-Print Network [OSTI]

The Complexity of Forecast Testing Lance Fortnow # Rakesh V. Vohra + Abstract Consider a weather forecaster predicting a probability of rain for the next day. We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster. Sandroni shows that any test

Fortnow, Lance

226

Does increasing model stratospheric resolution improve extended range forecast skill?  

E-Print Network [OSTI]

Does increasing model stratospheric resolution improve extended range forecast skill? Greg Roff,1 forecast skill at high Southern latitudes is explored. Ensemble forecasts are made for two model configurations that differ only in vertical resolution above 100 hPa. An ensemble of twelve 30day forecasts

227

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect (OSTI)

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

228

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network [OSTI]

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural demand time series based only on data for six years to forecast the demand for the seventh year. Both networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system

Abdel-Aal, Radwan E.

229

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network [OSTI]

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

230

Strategic safety stocks in supply chains with evolving forecasts  

E-Print Network [OSTI]

we have an evolving demand forecast. Under assumptions about the forecasts, the demand process their supply chain operations based on a forecast of future demand over some planning horizon. Furthermore stock inventory in a supply chain that is subject to a dynamic, evolving demand forecast. In particular

Graves, Stephen C.

231

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST Energy Demand 2008-2018 forecast supports the analysis and recommendations of the 2007 Integrated Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly

232

Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)  

SciTech Connect (OSTI)

This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

233

Mark Johnson | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen OwnedofDepartment ofJared Temanson -ofMarc Morial - PresidentEnergyMark

234

Mark Higgins | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion | Department of EnergyDevelopment Accident Tolerant Fuel: FeCrAlMark Elless, Ph.D.

235

Los Alamos National Laboratory marks  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces and Interfaces Sample6,LocalNuclearand LANSdescribesMay 14,marks 20 years

236

Mark Whitney | Department of Energy  

Energy Savers [EERE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |EnergyonSupport0.pdf5 OPAM SEMIANNUAL REPORTMA EnergyMagna1983:Marine andMark HigginsWhitney

237

Mark Lausten | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Year in3.pdfEnergy HealthComments MEMA: CommentsEnergy 13, 1968:CampMarissaMark Lausten

238

Molecular Simulation of Nanofluids Mark J. Biggs  

E-Print Network [OSTI]

Molecular Simulation of Nanofluids Mark J. Biggs School of Chemical Engineering, The University of Adelaide, South Australia, Australia, 5005. mark.biggs@adelaide.edu.au Models of nanofluid systems ­ which

Adler, Joan

239

Labour Relations Research Collection / Mark Thompson (collector)  

E-Print Network [OSTI]

Labour Relations Research Collection / Mark Thompson (collector) Compiled by Erwin Wodarczak (2004 of Contents Collection Description o Title / Dates of Creation / Physical Description o Collector catalogue) #12;Collection Description Labour Relations Research Collection / Mark Thompson (collector

Handy, Todd C.

240

Computational Sciences and Engineering Division | ornl.gov  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Computational Sciences and Engineering Division SHARE Computational Sciences and Engineering Division The Computational Sciences and Engineering Division is a major research...

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Computer Sciences and Mathematics Division | ornl.gov  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Computer Sciences and Mathematics Division SHARE Computer Sciences and Mathematics Division The Computer Science and Mathematics Division (CSMD) is ORNL's premier source of basic...

242

SolarAnywhere forecast (Perez & Hoff) This chapter describes, and presents an evaluation of, the forecast models imbedded in the  

E-Print Network [OSTI]

SolarAnywhere forecast (Perez & Hoff) ABSTRACT This chapter describes, and presents an evaluation of, the forecast models imbedded in the SolarAnywhere platform. The models include satellite derived cloud motion based forecasts for the short to medium horizon (1 5 hours) and forecasts derived from NOAA

Perez, Richard R.

243

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

J.B. , 2004: Probabilistic wind power forecasts using localforecast intervals for wind power output using NWP-predictedsources such as wind and solar power. Integration of this

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

244

Advanced Numerical Weather Prediction Techniques for Solar Irradiance Forecasting : : Statistical, Data-Assimilation, and Ensemble Forecasting  

E-Print Network [OSTI]

United States California Solar Initiative Coastally Trappedparticipants in the California Solar Initiative (CSI)on location. In California, solar irradiance forecasts near

Mathiesen, Patrick James

2013-01-01T23:59:59.000Z

245

Primary Marks Secondary Marks Word Mark Word Mark Word Mark UCI-00013A UCI-00019A UCI-00025AUCI-00007AUCI-00001A  

E-Print Network [OSTI]

-00012AUCI-00006A 1000 White TBD TBD 1800 White TBD TBD Madeira RA Brand: University of California permitted: Cross licensing with other marks permitted: NO USE of current player's names, image or likeness with PMS 7685. Brand: University of California, Irvine Colors: Pantone Verbiage: PMS Black White PMS 123

Rose, Michael R.

246

Wind Speed Forecasting for Power System Operation  

E-Print Network [OSTI]

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

Zhu, Xinxin

2013-07-22T23:59:59.000Z

247

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network [OSTI]

Appendix A: Fuel Price Forecast Introduction ................................................................................................................... 17 INTRODUCTION Since the millennium, the trend for fuel prices has been one of uncertainty prices, which have traditionally been relatively stable, increased by about 50 percent in 2008. Fuel

248

Essays in International Macroeconomics and Forecasting  

E-Print Network [OSTI]

This dissertation contains three essays in international macroeconomics and financial time series forecasting. In the first essay, I show, numerically, that a two-country New-Keynesian Sticky Prices model, driven by monetary and productivity shocks...

Bejarano Rojas, Jesus Antonio

2012-10-19T23:59:59.000Z

249

Dynamic Algorithm for Space Weather Forecasting System  

E-Print Network [OSTI]

for the designation as UNDERGRADUATE RESEARCH SCHOLAR April 2010 Major: Nuclear Engineering DYNAMIC ALGORITHM FOR SPACE WEATHER FORECASTING SYSTEM A Junior Scholars Thesis by LUKE DUNCAN FISCHER Submitted to the Office of Undergraduate... 2010 Major: Nuclear Engineering iii ABSTRACT Dynamic Algorithm for Space Weather Forecasting System. (April 2010) Luke Duncan Fischer Department of Nuclear Engineering Texas A&M University Research Advisor: Dr. Stephen Guetersloh...

Fischer, Luke D.

2011-08-08T23:59:59.000Z

250

Environmental Transport Division: 1979 report  

SciTech Connect (OSTI)

During 1979, the Environmental Transport Division (ETD) of the Savannah River Laboratory conducted atmospheric, terrestrial, aquatic, and marine studies, which are described in a series of articles. Separate abstracts were prepared for each. Publications written about the 1979 research are listed at the end of the report.

Murphy, C.E. Jr.; Schubert, J.F.; Bowman, W.W.; Adams, S.E.

1980-03-01T23:59:59.000Z

251

Education Strategy Team Policy Division  

E-Print Network [OSTI]

Education Strategy Team Policy Division DFID 1 Palace Street London SW1E 5HE 30 October 2009 TEL fellowships in India under the Wellcome Trust/DBT India Alliance2 . We believe that such investment is vital/Global-health-research/WTX055734.htm 2 Wellcome Trust/DBT India Alliance: http://www.wellcomedbt.org/index.htm #12;to support

Rambaut, Andrew

252

Publishing Division The Edinburgh Building  

E-Print Network [OSTI]

Publishing Division The Edinburgh Building Shaftesbury Road Cambridge CB2 2RU, UK TELEPHONE 01223 Building, Cambridge CB2 2RU, UK 40 West 20th Street, New York NY 10011-4211, USA 477 Williamstown Road Record [1] walter carl hartwig 2 The origin of primates [5] david tab rasmussen The earliest primates

Rosenberger, Alfred H.

253

Nambe Pueblo Water Budget and Forecasting model.  

SciTech Connect (OSTI)

This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

Brainard, James Robert

2009-10-01T23:59:59.000Z

254

DIVISION 6 -WOOD AND PLASTICS 06000 GENERAL  

E-Print Network [OSTI]

DIVISION 6 - WOOD AND PLASTICS ________________________________________________________________________ 06000 GENERAL 1. For both woods and plastics, special attention is called to matters of flame spread-dried. 3. For exterior wood or plastic framed structures, see Division 4 for dimensions of Sample Panel

255

Westinghouse Advanced Reactors Division Plutonium Fuel Laboratories  

Office of Legacy Management (LM)

Radiological Condition of the Westinghouse Advanced Reactors Division Plutonium Fuel Laboratories Cheswick, Pennsylvania -. -, -- AGENCY: Office of Operational Safety, Department...

256

EARTH SCIENCES Lower-Division Requirements  

E-Print Network [OSTI]

2012-2013 EARTH SCIENCES Lower-Division Requirements Math 20A_____ 20B_____ 20C_____ 20D (BILD 3) _____ SIO 50* _____ Group A: Earth Science Upper-Division Core Requirements (all courses _____ Introduction to Geophysics SIO 104 _____ Paleobiology and History of Life* Group B: Upper-Division Earth

Constable, Steve

257

Finance Division EXTRA MILE AWARD PROGRAM  

E-Print Network [OSTI]

Finance Division EXTRA MILE AWARD PROGRAM Nomination Form Instructions Any fulltime or parttime permanent or temporary SPA employee within the Finance Division who works 20 or more provided. The seven major departments within the Finance Division to choose from are described below

Crews, Stephen

258

Analytical Chemistry Division's sample transaction system  

SciTech Connect (OSTI)

The Analytical Chemistry Division uses the DECsystem-10 computer for a wide range of tasks: sample management, timekeeping, quality assurance, and data calculation. This document describes the features and operating characteristics of many of the computer programs used by the Division. The descriptions are divided into chapters which cover all of the information about one aspect of the Analytical Chemistry Division's computer processing.

Stanton, J.S.; Tilson, P.A.

1980-10-01T23:59:59.000Z

259

The Division of Biology & Biomedical Sciences  

E-Print Network [OSTI]

The Division of Biology & Biomedical Sciences what will YOU discover? #12;620students more than 470faculty 36departments 12programs and one YOU. DBBS Division of Biology and Biomedical Sciences Washington. The Division of Biology and Biomedical Sciences (DBBS) is ideally positioned to foster the interdisciplinary

Kornfeld, S. Kerry

260

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast  

E-Print Network [OSTI]

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast Summary............................................................................................................ 2 Sixth Power Plan Demand Forecast................................................................................................ 4 Demand Forecast Range

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
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to obtain the most current and comprehensive results.


261

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast  

E-Print Network [OSTI]

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

262

Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint  

SciTech Connect (OSTI)

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

2014-05-01T23:59:59.000Z

263

FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2  

SciTech Connect (OSTI)

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

Templeton, K.J.

1996-05-23T23:59:59.000Z

264

MATERIALS AND MOLECULAR RESEARCH DIVISION. ANNUAL REPORT 1980  

E-Print Network [OSTI]

of trans uranium organometallic chemistry, particularlyfor Uranium Isotope Separation," Chemistry Division, IsotopeOlander, "Uranium Enrichment by Laser," Chemistry Division,

Searcy, Alan W.

2010-01-01T23:59:59.000Z

265

analytical sciences division: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Division Environmental Management and Restoration Websites Summary: Chemical Sciences and Engineering Division Director Assoc Director Ops Assoc Director Science Yates...

266

Health, Safety, and Environment Division  

SciTech Connect (OSTI)

The primary responsibility of the Health, Safety, and Environmental (HSE) Division at the Los Alamos National Laboratory is to provide comprehensive occupational health and safety programs, waste processing, and environmental protection. These activities are designed to protect the worker, the public, and the environment. Meeting these responsibilities requires expertise in many disciplines, including radiation protection, industrial hygiene, safety, occupational medicine, environmental science and engineering, analytical chemistry, epidemiology, and waste management. New and challenging health, safety, and environmental problems occasionally arise from the diverse research and development work of the Laboratory, and research programs in HSE Division often stem from these applied needs. These programs continue but are also extended, as needed, to study specific problems for the Department of Energy. The results of these programs help develop better practices in occupational health and safety, radiation protection, and environmental science.

Wade, C [comp.] [comp.

1992-01-01T23:59:59.000Z

267

NREL: Biomass Research - Mark R. Nimlos  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

R. Nimlos Mark Nimlos is a Principal Scientist and Supervisor for the Biomass Molecular Sciences group in the National Bioenergy Center at the National Renewable Energy Laboratory....

268

Autoregressive Time Series Forecasting of Computational Demand  

E-Print Network [OSTI]

We study the predictive power of autoregressive moving average models when forecasting demand in two shared computational networks, PlanetLab and Tycoon. Demand in these networks is very volatile, and predictive techniques to plan usage in advance can improve the performance obtained drastically. Our key finding is that a random walk predictor performs best for one-step-ahead forecasts, whereas ARIMA(1,1,0) and adaptive exponential smoothing models perform better for two and three-step-ahead forecasts. A Monte Carlo bootstrap test is proposed to evaluate the continuous prediction performance of different models with arbitrary confidence and statistical significance levels. Although the prediction results differ between the Tycoon and PlanetLab networks, we observe very similar overall statistical properties, such as volatility dynamics.

Sandholm, Thomas

2007-01-01T23:59:59.000Z

269

Chemical Sciences and Engineering Division  

E-Print Network [OSTI]

· Heterogeneous and Homogenous Catalysis · Fuel Cell and Electrocatalysis Electrochemical Energy Storage Anthony Burrell · Materials Research · Technology Develop- ment · Engineering Research · Electrochemical Analysis Frontier Research Centers M. Thackeray C. Marshall Approved: ____________________________2/24/14 Mark

Kemner, Ken

270

Do Investors Forecast Fat Firms? Evidence from the Gold Mining Industry  

E-Print Network [OSTI]

Economists Gold Price Forecasts, Australian Journal ofDo Investors Forecast Fat Firms? Evidence from the Gold

Borenstein, Severin; Farrell, Joseph

2006-01-01T23:59:59.000Z

271

Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management  

E-Print Network [OSTI]

Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...

Datta, Shoumen

2008-07-31T23:59:59.000Z

272

Market perceptions of efficiency and news in analyst forecast errors  

E-Print Network [OSTI]

Financial analysts are considered inefficient when they do not fully incorporate relevant information into their forecasts. In this dissertation, I investigate differences in the observable efficiency of analysts' earnings forecasts between firms...

Chevis, Gia Marie

2004-11-15T23:59:59.000Z

273

The effect of multinationality on management earnings forecasts  

E-Print Network [OSTI]

This study examines the relationship between a firm??s degree of multinationality and its managers?? earnings forecasts. Firms with a high degree of multinationality are subject to greater uncertainty regarding earnings forecasts due...

Runyan, Bruce Wayne

2005-08-29T23:59:59.000Z

274

Wind power forecasting in U.S. electricity markets.  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

275

Wind power forecasting in U.S. Electricity markets  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

276

Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)  

SciTech Connect (OSTI)

This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

Hodge, B. M.; Milligan, M.

2011-07-01T23:59:59.000Z

277

0 20 4010 Miles NOAA Harmful Algal Bloom Operational Forecast System  

E-Print Network [OSTI]

0 20 4010 Miles NOAA Harmful Algal Bloom Operational Forecast System Texas Forecast Region Maps to Sargent BCH NOAA Harmful Algal Bloom Operational Forecast System Texas Forecast Region Maps 0 5 102 Bloom Operational Forecast System Texas Forecast Region Maps 0 5 102.5 Miles West Bay #12;Aransas Bay

278

Credit Documentation and the Mark 15 Subroutine  

SciTech Connect (OSTI)

This report documents the rewrite of the heat transfer subroutine. Part of the process of preparing the Mark 15 assembly for production operation is the development of thermal-hydraulic limits for the assembly. These limits require, among other items, the development of a Mark 15 assembly subroutine for the CREDIT code.

McAllister, J.E.

2001-08-16T23:59:59.000Z

279

UNDERWATER PAINT MARKING OF PORPOISES1  

E-Print Network [OSTI]

UNDERWATER PAINT MARKING OF PORPOISES1 Identification of individual animals has always been, and that was easy to apply at sea. Even a temporary mark permitting positive iden- tification for only a few hours would be a boon. Paint seemed an answer (Schevill 1966). Materials and Methods Several standard paint

280

Autonomy for Aurora's Mars Missions Mark Woods,  

E-Print Network [OSTI]

Autonomy for Aurora's Mars Missions Mark Woods, SciSys Ltd., Clothier Road, Bristol, UK BS4 5SS Email: mark.woods@scisys.co.uk Tel: +44 117 9717251 ESA's Aurora programme incorporates a strategy for European involvement in future robotic and human exploration of our Solar System. The Aurora roadmap calls

Fisher, Michael

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

WASHINGTON --Budget experts gave high marks for courage and low marks for  

E-Print Network [OSTI]

WASHINGTON -- Budget experts gave high marks for courage and low marks for the details in a bold-Wis., chairman of the House Budget Committee, would reverse retirement policies that became staples of American

Patzek, Tadeusz W.

282

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

283

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network [OSTI]

requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

284

Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1  

E-Print Network [OSTI]

Using Bayesian Model Averaging to Calibrate Forecast Ensembles 1 Adrian E. Raftery, Fadoua forecasting often exhibit a spread-skill relationship, but they tend to be underdispersive. This paper of PDFs centered around the individual (possibly bias-corrected) forecasts, where the weights are equal

Washington at Seattle, University of

285

Forecast Combinations of Computational Intelligence and Linear Models for the  

E-Print Network [OSTI]

Forecast Combinations of Computational Intelligence and Linear Models for the NN5 Time Series Forecasting competition Robert R. Andrawis Dept Computer Engineering Cairo University, Giza, Egypt robertrezk@eg.ibm.com November 6, 2010 Abstract In this work we introduce a forecasting model with which we participated

Atiya, Amir

286

GET your forecast at the click of a button.  

E-Print Network [OSTI]

GET your forecast at the click of a button. EXPLORE your local weather in detail. PLAN your days favourite locations; · Pan and zoom to any area in Australia; · Combine the latest weather and forecast current temperatures across Australia. MetEyeTM computer screen image displaying the weather forecast

Greenslade, Diana

287

Compatibility of Stand Basal Area Predictions Based on Forecast Combination  

E-Print Network [OSTI]

Compatibility of Stand Basal Area Predictions Based on Forecast Combination Xiongqing Zhang Carr.) in Beijing, forecast combination was used to adjust predicted stand basal areas from these three types of models. The forecast combination method combines information and disperses errors from

Cao, Quang V.

288

MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY  

E-Print Network [OSTI]

MOUNTAIN WEATHER PREDICTION: PHENOMENOLOGICAL CHALLENGES AND FORECAST METHODOLOGY Michael P. Meyers of the American Meteorological Society Mountain Weather and Forecasting Monograph Draft from Friday, May 21, 2010 of weather analysis and forecasting in complex terrain with special emphasis placed on the role of humans

Steenburgh, Jim

289

WP1: Targeted and informative forecast system design  

E-Print Network [OSTI]

WP1: Targeted and informative forecast system design Emma Suckling, Leonard A. Smith and David Stainforth EQUIP Meeting ­ August 2011 Edinburgh #12;Targeted and informative forecast system design Develop models to support decision making (1.4) #12;Targeted and informative forecast system design KEY QUESTIONS

Stevenson, Paul

290

Earnings forecast bias -a statistical analysis Franois Dossou  

E-Print Network [OSTI]

Earnings forecast bias - a statistical analysis François Dossou Sandrine Lardic** Karine Michalon' earnings forecasts is an important aspect of research for different reasons: Many empirical studies employ analysts' consensus forecasts as a proxy for the market's expectations of future earnings in order

Paris-Sud XI, Université de

291

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta*  

E-Print Network [OSTI]

Using Large Datasets to Forecast Sectoral Employment Rangan Gupta* Department of Economics Bayesian and classical methods to forecast employment for eight sectors of the US economy. In addition-sample period and January 1990 to March 2009 as the out-of- sample horizon, we compare the forecast performance

Ahmad, Sajjad

292

Power load forecasting Organization: Huizhou Electric Power, P. R. China  

E-Print Network [OSTI]

Power load forecasting Organization: Huizhou Electric Power, P. R. China Presenter: Zhifeng Hao can be divided into load forecasting and electrical consumption predicting according to forecasting in generators macroeconomic control, power exchange plan and so on. And the prediction is from one day to seven

293

Accuracy of near real time updates in wind power forecasting  

E-Print Network [OSTI]

· advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

Heinemann, Detlev

294

Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1  

E-Print Network [OSTI]

1 Weighted Parametric Operational Hydrology Forecasting Thomas E. Croley II1 1 Great Lakes forecasts in operational hydrology builds a sample of possibilities for the future, of climate series from-parametric method can be extended into a new weighted parametric hydrological forecasting technique to allow

295

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

296

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption

297

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff in the Demand Analysis. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data

298

Draft for Public Comment Appendix A. Demand Forecast  

E-Print Network [OSTI]

Draft for Public Comment A-1 Appendix A. Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required component of the Council's Northwest Regional Conservation had a tradition of acknowledging the uncertainty of any forecast of electricity demand and developing

299

Forecasting Market Demand for New Telecommunications Services: An Introduction  

E-Print Network [OSTI]

Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc to redress this situation by presenting a discussion of the issues involved in demand forecasting for new or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica­ tions Services. 1 #12

McBurney, Peter

300

Using Belief Functions to Forecast Demand for Mobile Satellite Services  

E-Print Network [OSTI]

Using Belief Functions to Forecast Demand for Mobile Satellite Services Peter McBurney and Simon.j.mcburney,s.d.parsonsg@elec.qmw.ac.uk Abstract. This paper outlines an application of belief functions to forecasting the demand for a new service in a new category, based on new technology. Forecasting demand for a new product or service

McBurney, Peter

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE -APRIL 2014  

E-Print Network [OSTI]

CSUF ECONOMIC OUTLOOK AND FORECASTS MIDYEAR UPDATE - APRIL 2014 Anil Puri, Ph.D. -- Director, Center for Economic Analysis and Forecasting -- Dean, Mihaylo College of Business and Economics Mira Farka, Ph.D. -- Co-Director, Center for Economic Analysis and Forecasting -- Associate Professor

de Lijser, Peter

302

A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION  

E-Print Network [OSTI]

1 A BAYESIAN MODEL COMMITTEE APPROACH TO FORECASTING GLOBAL SOLAR RADIATION in the realm of solar radiation forecasting. In this work, two forecasting models: Autoregressive Moving. The very first results show an improvement brought by this approach. 1. INTRODUCTION Solar radiation

Boyer, Edmond

303

FORECASTING SOLAR RADIATION PRELIMINARY EVALUATION OF AN APPROACH  

E-Print Network [OSTI]

FORECASTING SOLAR RADIATION -- PRELIMINARY EVALUATION OF AN APPROACH BASED UPON THE NATIONAL, and undertake a preliminary evaluation of, a simple solar radiation forecast model using sky cover predictions forecasts is 0.05o in latitude and longitude. Solar Radiation model: The model presented in this paper

Perez, Richard R.

304

Jefferson Lab Divisions & Departments  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsingFunInfraredJefferson Lab Click on theJames D.AnnouncesWorldTherapy |Divisions

305

Chemical Technology Division annual technical report 1997  

SciTech Connect (OSTI)

The Chemical Technology (CMT) Division is a diverse technical organization with principal emphases in environmental management and development of advanced energy sources. The Division conducts research and development in three general areas: (1) development of advanced power sources for stationary and transportation applications and for consumer electronics, (2) management of high-level and low-level nuclear wastes and hazardous wastes, and (3) electrometallurgical treatment of spent nuclear fuel. The Division also performs basic research in catalytic chemistry involving molecular energy resources, mechanisms of ion transport in lithium battery electrolytes, and the chemistry of technology-relevant materials and electrified interfaces. In addition, the Division operates the Analytical Chemistry Laboratory, which conducts research in analytical chemistry and provides analytical services for programs at Argonne National Laboratory (ANL) and other organizations. Technical highlights of the Division`s activities during 1997 are presented.

NONE

1998-06-01T23:59:59.000Z

306

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network [OSTI]

capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

Lang, K.

1982-01-01T23:59:59.000Z

307

Issues in midterm analysis and forecasting, 1996  

SciTech Connect (OSTI)

This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

NONE

1996-08-01T23:59:59.000Z

308

Forecasting Turbulent Modes with Nonparametric Diffusion Models  

E-Print Network [OSTI]

This paper presents a nonparametric diffusion modeling approach for forecasting partially observed noisy turbulent modes. The proposed forecast model uses a basis of smooth functions (constructed with the diffusion maps algorithm) to represent probability densities, so that the forecast model becomes a linear map in this basis. We estimate this linear map by exploiting a previously established rigorous connection between the discrete time shift map and the semi-group solution associated to the backward Kolmogorov equation. In order to smooth the noisy data, we apply diffusion maps to a delay embedding of the noisy data, which also helps to account for the interactions between the observed and unobserved modes. We show that this delay embedding biases the geometry of the data in a way which extracts the most predictable component of the dynamics. The resulting model approximates the semigroup solutions of the generator of the underlying dynamics in the limit of large data and in the observation noise limit. We will show numerical examples on a wide-range of well-studied turbulent modes, including the Fourier modes of the energy conserving Truncated Burgers-Hopf (TBH) model, the Lorenz-96 model in weakly chaotic to fully turbulent regimes, and the barotropic modes of a quasi-geostrophic model with baroclinic instabilities. In these examples, forecasting skills of the nonparametric diffusion model are compared to a wide-range of stochastic parametric modeling approaches, which account for the nonlinear interactions between the observed and unobserved modes with white and colored noises.

Tyrus Berry; John Harlim

2015-01-27T23:59:59.000Z

309

Do quantitative decadal forecasts from GCMs provide  

E-Print Network [OSTI]

' · Empirical models quantify our ability to predict without knowing the laws of physics · Climatology skill' model? 2. Dynamic climatology (DC) is a more appropriate benchmark for near- term (initialised) climate forecasts · A conditional climatology, initialised at launch and built from the historical archive

Stevenson, Paul

310

Issues in midterm analysis and forecasting 1998  

SciTech Connect (OSTI)

Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

NONE

1998-07-01T23:59:59.000Z

311

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS MARINE SERVICE  

E-Print Network [OSTI]

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS MARINE SERVICE IMPROVEMENTS FOR QUEENSLAND across Australia. FURTHER INFORMATION: www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 From © Copyright Commonwealth of Australia 2013, Bureau of Meteorology Queensland Australia Coastal Waters Zones

Greenslade, Diana

312

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

313

Forecasting sudden changes in environmental pollution patterns  

E-Print Network [OSTI]

Forecasting sudden changes in environmental pollution patterns María J. Olascoagaa,1 and George of Mexico in 2010. We present a methodology to predict major short-term changes in en- vironmental River's mouth in the Gulf of Mexico. The resulting fire could not be extinguished and the drilling rig

Olascoaga, Maria Josefina

314

Amending Numerical Weather Prediction forecasts using GPS  

E-Print Network [OSTI]

to validate the amounts of humidity in Numerical Weather Prediction (NWP) model forecasts. This paper presents. Satellite images and Numerical Weather Prediction (NWP) models are used together with the synoptic surface. In this paper, a case is presented for which the operational Numerical Weather Prediction Model (NWP) HIRLAM

Stoffelen, Ad

315

Prediction versus Projection: How weather forecasting and  

E-Print Network [OSTI]

Prediction versus Projection: How weather forecasting and climate models differ. Aaron B. Wilson Context: Global http://data.giss.nasa.gov/ #12;Numerical Weather Prediction Collect Observations alters associated weather patterns. Models used to predict weather depend on the current observed state

Howat, Ian M.

316

Facebook IPO updated valuation and user forecasting  

E-Print Network [OSTI]

Facebook IPO updated valuation and user forecasting Based on: Amendment No. 6 to Form S-1 (May 9. Peter Cauwels and Didier Sornette, Quis pendit ipsa pretia: facebook valuation and diagnostic Extreme Growth JPMPaper Cauwels and Sornette 840 1110 1820 S1- filing- May 9 2012 1006 1105 1371 Facebook

317

FORECAST OF VACANCIES Until end of 2016  

E-Print Network [OSTI]

#12;FORECAST OF VACANCIES Until end of 2016 (Issue No. 22) #12;Page 2 OVERVIEW OF BASIC REQUIREMENTS FOR PROFESSIONAL VACANCIES IN THE IAEA Education, Experience and Skills: Professional staff the team of professionals. Second half 2015 VACANCY GRADE REQUIREMENTS / ROLE EXPECTED DATE OF VACANCY

318

Segmenting Time Series for Weather Forecasting  

E-Print Network [OSTI]

) models is summarised as weather forecast texts. In the domain of gas turbines, sensor data from an operational gas turbine is summarised for the maintenance engineers. More details on SUMTIME have been to develop a generic model for summarisation of time series data. Initially, we have applied standard

Sripada, Yaji

319

Online short-term solar power forecasting  

SciTech Connect (OSTI)

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

320

EARTH SCIENCES DIVISION ANNUAL REPORT 1978  

E-Print Network [OSTI]

of Energy's Division of Geothermal Energy has undertaken aand Ghormley, E. L. , 1976. Geothermal energy conversion andsuch diverse areas as geothermal energy, oil recovery, in-

Authors, Various

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

EARTH SCIENCES DIVISION. ANNUAL REPORT 1977.  

E-Print Network [OSTI]

8erkeley Laboratory (LBL), the Earth Sciences Division, wasactivation analysis: rare earth element distribution (D)can be used to generate earth- quake records for use in

Witherspoon, P.A.

2011-01-01T23:59:59.000Z

322

Supervisory General Engineer (Facility Engineering Division Director)  

Broader source: Energy.gov [DOE]

A successful candidate in this position will lead the Facility Engineering Division by providing internal and independent safety system oversight of Waste Isolation Pilot Plant (WIPP) operations in...

323

Colorado Air Pollution Control Division - Construction Permits...  

Open Energy Info (EERE)

Jump to: navigation, search OpenEI Reference LibraryAdd to library Web Site: Colorado Air Pollution Control Division - Construction Permits Forms and Air Pollutant Emission...

324

X-Ray Science Division (XSD)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

X-Ray Science Division (XSD) Search Button About Welcome Overview Visiting the APS Mission & Goals Find People Organization Charts Committees Job Openings User Information...

325

Enforcement Letter, Westinghouse Waste Isolation Division - October...  

Broader source: Energy.gov (indexed) [DOE]

Division related to four noncompliances with the requirements of the Quality Assurance Rule andor the Occupational Radiation Protection Rule at DOE's Waste Isolation...

326

Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power  

E-Print Network [OSTI]

Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price as traded on the wholesale, short-term (spot) market at the Mid-Columbia trading hub. This price represents noted. BASE CASE FORECAST The base case wholesale electricity price forecast uses the Council's medium

327

FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2  

SciTech Connect (OSTI)

For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

Valero, O.J.

1996-04-23T23:59:59.000Z

328

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

329

Forecastability as a Design Criterion in Wind Resource Assessment: Preprint  

SciTech Connect (OSTI)

This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

Zhang, J.; Hodge, B. M.

2014-04-01T23:59:59.000Z

330

Mark Jankowski: Minnesota Pollution Control Agency  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartmentMark H.MarkMark

331

School of Art Division of Graphic Design  

E-Print Network [OSTI]

.372.7763 419.372.6955 fax lyoung@bgsu.edu www.bgsu.edu/art BOWLING GREEN STATE UNIVERSITY Division of Graphic.bgsu.edu/art BOWLING GREEN STATE UNIVERSITY 1) Be of Junior (60+ hours) or Senior (90+ hours) standing withinSchool of Art Division of Graphic Design 1020 Fine Arts Center Bowling Green, Ohio 43403-0204 419

Moore, Paul A.

332

Satellite Meteorology and Climatology Division Roadmap  

E-Print Network [OSTI]

Satellite Meteorology and Climatology Division Roadmap NOAA NESDIS Center for Satellite Applications and Research #12;SMCD Roadmap 2 NOAA/NESDIS/STAR Satellite Meteorology and Climatology Division Roadmap September 2005 NOAA Science Center, 5200 Auth Road, Room 712, Camp Springs, MD 20746 #12;SMCD

Kuligowski, Bob

333

Materials Sciences Division 1990 annual report  

SciTech Connect (OSTI)

This report is the Materials Sciences Division`s annual report. It contains abstracts describing materials research at the National Center for Electron Microscopy, and for research groups in metallurgy, solid-state physics, materials chemistry, electrochemical energy storage, electronic materials, surface science and catalysis, ceramic science, high tc superconductivity, polymers, composites, and high performance metals.

Not Available

1990-12-31T23:59:59.000Z

334

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 2 of this administrative procedure has been posted on the WVU Division of Human Resources Web page hr.wvu.edu. In the event

Mohaghegh, Shahab

335

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 2 Access been posted on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict

Mohaghegh, Shahab

336

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 2 Employment been posted on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict

Mohaghegh, Shahab

337

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 2 been posted on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict

Mohaghegh, Shahab

338

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

on the WVU Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 3 Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted

Mohaghegh, Shahab

339

EMS Division Potential Benefits of Selected  

E-Print Network [OSTI]

driven by a high speed gas turbine supplied power to a 400 HP superconductive homopolar motor during at Overcome by New Technology: Cryocoolers & Cu Fiber brushes2 #12;EMS Division Baseline with Multi-turn Field Coil Multi-turn Armature Cryostat Steel Flux Return #12;EMS Division Homopolar Motor Technology

340

Fixed Income Division Nomura International plc  

E-Print Network [OSTI]

Fixed Income Division © Nomura International plc Symmetry methods for quadratic Gaussian models International plc Outline Motivation The quadratic Gaussian distribution The quadratic Gaussian process The quadratic Gaussian model #12;Fixed Income Division 3© Nomura International plc Part 1 Motivation #12;Fixed

Macrina, Andrea

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Nuclear Engineering Division Irradiated Materials Laboratory  

E-Print Network [OSTI]

Nuclear Engineering Division Irradiated Materials Laboratory The Irradiated Materials Laboratory (IML) in Argonne's Nuclear Engineering Division is used to conduct research on the behavior. #12;C O N TA C T > Dr. Michael C. Billone | 630-252-7146 | billone@anl.gov | Nuclear Engineering

Kemner, Ken

342

The Division of Biology & Biomedical Sciences  

E-Print Network [OSTI]

The Division of Biology & Biomedical Sciences what will you discover? #12;what will you discover and Biomedical Sciences Washington University in St. Louis dbbs.wustl.edu On the cover: Moshi Song (left of other disciplines. The Division of Biology and Biomedical Sciences is ideally positioned to foster

Stormo, Gary

343

LIST OF JOURNAL PUBLICATIONS Mark Aindow  

E-Print Network [OSTI]

1 LIST OF JOURNAL PUBLICATIONS Mark Aindow 1987 1. Hexagonal Crystallography and Interphase, J Micros Res Tech 23: 98-99 (1992). 10. The Use of Electrochemical Scanning Tunneling Microscopy

Alpay, S. Pamir

344

Physics division annual report 2005.  

SciTech Connect (OSTI)

This report highlights the research performed in 2005 in the Physics Division of Argonne National Laboratory. The Division's programs include operation of ATLAS as a national user facility, nuclear structure and reaction research, nuclear theory, medium energy nuclear research and accelerator research and development. The mission of Nuclear Physics is to understand the origin, evolution and structure of baryonic matter in the universe--the matter that makes up stars, planets and human life itself. The Division's research focuses on innovative new ways to address this mission and 2005 was a year of great progress. One of the most exciting developments is the initiation of the Californium Rare Ion Breeder Upgrade, CARIBU. By combining a Cf-252 fission source, the gas catcher technology developed for rare isotope beams, a high-resolution isobar separator, and charge breeding ECR technology, CARIBU will make hundreds of new neutron-rich isotope beams available for research. The cover illustration shows the anticipated intensities of low-energy beams that become available for low-energy experiments and for injection into ATLAS for reacceleration. CARIBU will be completed in early 2009 and provide us with considerable experience in many of the technologies developed for a future high intensity exotic beam facility. Notable results in research at ATLAS include a measurement of the isomeric states in {sup 252}No that helps pin down the single particle structure expected for superheavy elements, and a new low-background measurement of {sup 16}N beta-decay to determine the {sup 12}C({alpha},{gamma}){sup 16}O reaction rate that is so important in astrophysical environments. Precise mass measurements shed new light on the unitarity of the quark weak-mixing matrix in the search for physics beyond the standard model. ATLAS operated for 4686 hours of research in FY2005 while achieving 95% efficiency of beam delivery for experiments. In Medium-Energy Physics, radium isotopes were trapped in an atom trap for the first time, a major milestone in an innovative search for the violation of time-reversal symmetry. New results from HERMES establish that strange quarks carry little of the spin of the proton and precise results have been obtained at JLAB on the changes in quark distributions in light nuclei. New theoretical results reveal that the nature of the surfaces of strange quark stars. Green's function Monte Carlo techniques have been extended to scattering problems and show great promise for the accurate calculation, from first principles, of important astrophysical reactions. Flame propagation in type 1A supernova has been simulated, a numerical process that requires considering length scales that vary by factors of eight to twelve orders of magnitude. Argonne continues to lead in the development and exploitation of the new technical concepts that will truly make an advanced exotic beam facility, in the words of NSAC, 'the world-leading facility for research in nuclear structure and nuclear astrophysics'. Our science and our technology continue to point the way to this major advance. It is a tremendously exciting time in science for these new capabilities hold the keys to unlocking important secrets of nature. The great progress that has been made in meeting the exciting intellectual challenges of modern nuclear physics reflects the talents and dedication of the Physics Division staff and the visitors, guests and students who bring so much to the research.

Glover, J.; Physics

2007-03-12T23:59:59.000Z

345

1998 Chemical Technology Division Annual Technical Report.  

SciTech Connect (OSTI)

The Chemical Technology (CMT) Division is a diverse technical organization with principal emphases in environmental management and development of advanced energy sources. The Division conducts research and development in three general areas: (1) development of advanced power sources for stationary and transportation applications and for consumer electronics, (2) management of high-level and low-level nuclear wastes and hazardous wastes, and (3) electrometallurgical treatment of spent nuclear fuel. The Division also performs basic research in catalytic chemistry involving molecular energy resources, mechanisms of ion transport in lithium battery electrolytes, and the chemistry of technology-relevant materials. In addition, the Division operates the Analytical Chemistry Laboratory, which conducts research in analytical chemistry and provides analytical services for programs at Argonne National Laboratory (ANL) and other organizations. Technical highlights of the Division's activities during 1998 are presented.

Ackerman, J.P.; Einziger, R.E.; Gay, E.C.; Green, D.W.; Miller, J.F.

1999-08-06T23:59:59.000Z

346

Test application of a semi-objective approach to wind forecasting for wind energy applications  

SciTech Connect (OSTI)

The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

Wegley, H.L.; Formica, W.J.

1983-07-01T23:59:59.000Z

347

Chemical and Laser Sciences Division annual report 1989  

SciTech Connect (OSTI)

The Chemical and Laser Sciences Division Annual Report includes articles describing representative research and development activities within the Division, as well as major programs to which the Division makes significant contributions.

Haines, N. (ed.)

1990-06-01T23:59:59.000Z

348

Forecasting hotspots using predictive visual analytics approach  

SciTech Connect (OSTI)

A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

2014-12-30T23:59:59.000Z

349

Solar Wind Forecasting with Coronal Holes  

E-Print Network [OSTI]

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

350

A survey on wind power ramp forecasting.  

SciTech Connect (OSTI)

The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-02-23T23:59:59.000Z

351

Table 23. Coal Receipts at Coke Plants by Census Division  

U.S. Energy Information Administration (EIA) Indexed Site

Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2014 Table 23. Coal Receipts at Coke Plants by Census Division...

352

Earth Sciences Division Research Summaries 2006-2007  

E-Print Network [OSTI]

the commencement of the Earth Sciences Division 30 yearstelling. Happy Anniversary! Earth Sciences Division ears YTritium in Engineered and Earth Materials Stefan Finsterle,

DePaolo, Donald

2008-01-01T23:59:59.000Z

353

FW: Mark Sogge USGS -subsea oil plume Marcia K McNutt 0 mark_sogge  

E-Print Network [OSTI]

Mark - FW: Mark Sogge USGS - subsea oil plume t Marcia K McNutt 0 mark_sogge Cc: Catherine Cesnik - subsea oil plume Just got a heads-up that a USGS employee is getting involved in the subsea oil plume is the Flagstaff Field Center Chief of Staff. This is the first I've heard of any USGS involvement in the subsea

Fleskes, Joe

354

Physics Division annual report 2004.  

SciTech Connect (OSTI)

This report highlights the research performed in 2004 in the Physics Division of Argonne National Laboratory. The Division's programs include operation of ATLAS as a national user facility, nuclear structure and reaction research, nuclear theory, medium energy nuclear research and accelerator research and development. The intellectual challenges of this research represent some of the most fundamental challenges in modern science, shaping our understanding of both tiny objects at the center of the atom and some of the largest structures in the universe. A great strength of these efforts is the critical interplay of theory and experiment. Notable results in research at ATLAS include a measurement of the charge radius of He-6 in an atom trap and its explanation in ab-initio calculations of nuclear structure. Precise mass measurements on critical waiting point nuclei in the rapid-proton-capture process set the time scale for this important path in nucleosynthesis. An abrupt fall-off was identified in the subbarrier fusion of several heavy-ion systems. ATLAS operated for 5559 hours of research in FY2004 while achieving 96% efficiency of beam delivery for experiments. In Medium Energy Physics, substantial progress was made on a long-term experiment to search for the violation of time-reversal invariance using trapped Ra atoms. New results from HERMES reveal the influence of quark angular momentum. Experiments at JLAB search for evidence of color transparency in rho-meson production and study the EMC effect in helium isotopes. New theoretical results include a Poincare covariant description of baryons as composites of confined quarks and non-point-like diquarks. Green's function Monte Carlo techniques give accurate descriptions of the excited states of light nuclei and these techniques been extended to scattering states for astrophysics studies. A theoretical description of the phenomena of proton radioactivity has been extended to triaxial nuclei. Argonne continues to lead in the development and exploitation of the new technical concepts that will truly make RIA, in the words of NSAC, ''the world-leading facility for research in nuclear structure and nuclear astrophysics''. The performance standards for new classes of superconducting cavities continue to increase. Driver linac transients and faults have been analyzed to understand reliability issues and failure modes. Liquid-lithium targets were shown to successfully survive the full-power deposition of a RIA beam. Our science and our technology continue to point the way to this major advance. It is a tremendously exciting time in science for RIA holds the keys to unlocking important secrets of nature. The work described here shows how far we have come and makes it clear we know the path to meet these intellectual challenges. The great progress that has been made in meeting the exciting intellectual challenges of modern nuclear physics reflects the talents and dedication of the Physics Division staff and the visitors, guests and students who bring so much to the research.

Glover, J.

2006-04-06T23:59:59.000Z

355

Biology and Medicine Division: Annual report 1986  

SciTech Connect (OSTI)

The Biology and Medicine Division continues to make important contributions in scientific areas in which it has a long-established leadership role. For 50 years the Division has pioneered in the application of radioisotopes and charged particles to biology and medicine. There is a growing emphasis on cellular and molecular applications in the work of all the Division's research groups. The powerful tools of genetic engineering, the use of recombinant products, the analytical application of DNA probes, and the use of restriction fragment length polymorphic DNA are described and proposed for increasing use in the future.

Not Available

1987-04-01T23:59:59.000Z

356

Earth Sciences Division collected abstracts: 1979  

SciTech Connect (OSTI)

This report is a compilation of abstracts of papers, internal reports, and talks presented during 1979 at national and international meetings by members of the Earth Sciences Division, Lawrence Livermore Laboratory. The arrangement is alphabetical (by author). For a given report, a bibliographic reference appears under the name of each coauthor, but the abstract iself is given only under the name of the first author or the first Earth Sciences Division author. A topical index at the end of the report provides useful cross references, while indicating major areas of research interest in the Earth Sciences Division.

Henry, A.L.; Schwartz, L.L.

1980-04-30T23:59:59.000Z

357

Draft Fourth Northwest Conservation and Electric Power Plan, Appendix D ECONOMIC AND DEMAND FORECASTS  

E-Print Network [OSTI]

AND DEMAND FORECASTS INTRODUCTION AND SUMMARY Role of the Demand Forecast A demand forecast of at least 20 years is one of the explicit requirements of the Northwest Power Act. A demand forecast is, of course analysis. Because the future is inherently uncertain, the Council forecasts a range of future demand levels

358

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

SciTech Connect (OSTI)

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

359

Physics division annual report 1999  

SciTech Connect (OSTI)

This report summarizes the research performed in the past year in the Argonne Physics Division. The Division's programs include operation of ATLAS as a national heavy-ion user facility, nuclear structure and reaction research with beams of heavy ions, accelerator research and development especially in superconducting radio frequency technology, nuclear theory and medium energy nuclear physics. The Division took significant strides forward in its science and its initiatives for the future in the past year. Major progress was made in developing the concept and the technology for the future advanced facility of beams of short-lived nuclei, the Rare Isotope Accelerator. The scientific program capitalized on important instrumentation initiatives with key advances in nuclear science. In 1999, the nuclear science community adopted the Argonne concept for a multi-beam superconducting linear accelerator driver as the design of choice for the next major facility in the field a Rare Isotope Accelerator (WA) as recommended by the Nuclear Science Advisory Committee's 1996 Long Range Plan. Argonne has made significant R&D progress on almost all aspects of the design concept including the fast gas catcher (to allow fast fragmentation beams to be stopped and reaccelerated) that in large part defined the RIA concept the superconducting rf technology for the driver accelerator, the multiple-charge-state concept (to permit the facility to meet the design intensity goals with existing ion-source technology), and designs and tests of high-power target concepts to effectively deal with the full beam power of the driver linac. An NSAC subcommittee recommended the Argonne concept and set as tie design goal Uranium beams of 100-kwatt power at 400 MeV/u. Argonne demonstrated that this goal can be met with an innovative, but technically in-hand, design. The heavy-ion research program focused on GammaSphere, the premier facility for nuclear structure gamma-ray studies. One example of the ground-breaking research with Garnmasphere was the first study of the limits of stability with angular momentum in the shell stabilized nobelium isotopes. It was found that these heaviest nuclei could be formed at surprisingly high angular momentum, providing important new insight into the production mechanisms for super-heavy elements. Another focus continues to be experiments with short-lived beams for critical nuclear astrophysics applications. Measurements revealed that {sup 44}Ti is more readily destroyed in supernovae than was expected. Major progress was made in collecting and storing unstable ions in the Canadian Penning Trap. The technique of stopping and rapidly extracting ions from a helium gas cell led directly to the new paradigm in the production of rare isotope beams that became RIA. ATLAS provided a record 6046 hours of beam use for experiments in FY99. The facility pressed hard to support the heavy demands of the GammaSphere Research program but maintained an operational reliability of 93%. Of the 29 different isotopes provided as beams in FY99, radioactive beams of {sup 44}Ti and {sup 17}F comprised 6% of the beam time. The theoretical efforts in the Division made dramatic new strides in such topics as quantum Monte Carlo calculations of light nuclei to understand microscopic many-body forces in nuclei; QCD calculations based on the Dyson-Schwinger approach which were extended to baryon systems and finite temperatures and densities; the structure of heavy nuclei; and proton decay modes of nuclei far from stability. The medium-energy program continues to focus on new techniques to understand how the quark-gluon structure of matter impacts the structure of nuclei. The HERMES experiment began making measurements of the fraction of the spin of the nucleon carried by the glue. Drell-Yan experiments study the flavor composition of the sea of the proton. Experiments at Jefferson lab search for clues of QCD dynamics at the hadronic level. A major advance in trace isotope analysis was realized with pioneering work on Atom Trap Trace Analysis, exploitin

Thayer, K., ed.; Physics

2000-12-06T23:59:59.000Z

360

adams mark hotel: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Adams, Mark 7 Computational Support for Play Testing Game Sketches Adam M. Smith , Mark J. Nelson Fission and Nuclear Technologies Websites Summary: Computational...

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network [OSTI]

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

362

Western Area Power Administration Starting Forecast Month: Sierra...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

CVP Generation Project Use First Preference Purchases and Exchanges Base Resource February 2014 Twelve-Month Forecast of CVP Generation and Base Resource February 2014 January...

363

Western Area Power Administration Starting Forecast Month: Sierra...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Use First Preference Purchases and Exchanges Base Resource April 2014 Twelve-Month Forecast of CVP Generation and Base Resource April 2014 March 2015 Exceedence Level: 90% (Dry)...

364

Western Area Power Administration Starting Forecast Month: Sierra...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Preference Month CVP Generation Project Use First Preference Purchases and Exchanges Base Resource May 2014 Twelve-Month Forecast of CVP Generation and Base Resource May 2014 April...

365

Western Area Power Administration Starting Forecast Month: Sierra...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

based on Green Book ("Above Normal") values. Base Resource March 2014 Twelve-Month Forecast of CVP Generation and Base Resource March 2014 February 2015 Exceedence Level: 90%...

366

analytical energy forecasting: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

367

Wind Power Forecasting Error Distributions: An International Comparison; Preprint  

SciTech Connect (OSTI)

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

2012-09-01T23:59:59.000Z

368

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind...

369

Forecasting the underlying potential governing climatic time series  

E-Print Network [OSTI]

We introduce a technique of time series analysis, potential forecasting, which is based on dynamical propagation of the probability density of time series. We employ polynomial coefficients of the orthogonal approximation of the empirical probability distribution and extrapolate them in order to forecast the future probability distribution of data. The method is tested on artificial data, used for hindcasting observed climate data, and then applied to forecast Arctic sea-ice time series. The proposed methodology completes a framework for `potential analysis' of climatic tipping points which altogether serves anticipating, detecting and forecasting climate transitions and bifurcations using several independent techniques of time series analysis.

Livina, V N; Mudelsee, M; Lenton, T M

2012-01-01T23:59:59.000Z

370

Econometric model and futures markets commodity price forecasting  

E-Print Network [OSTI]

Versus CCll1rnercial Econometric M:ldels." Uni- versity ofWorking Paper No. 72 ECONOMETRIC ! 'econometric forecasts with the futures

Just, Richard E.; Rausser, Gordon C.

1979-01-01T23:59:59.000Z

371

Using Customers' Reported Forecasts to Predict Future Sales  

E-Print Network [OSTI]

Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery , Michael Trick Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213. nihat

Gordon, Geoffrey J.

372

The Mark II Vertex Drift Chamber  

SciTech Connect (OSTI)

We have completed constructing and begun operating the Mark II Drift Chamber Vertex Detector. The chamber, based on a modified jet cell design, achieves 30 {mu}m spatial resolution and <1000 {mu}m track-pair resolution in pressurized CO{sub 2} gas mixtures. Special emphasis has been placed on controlling systematic errors including the use of novel construction techniques which permit accurate wire placement. Chamber performance has been studied with cosmic ray tracks collected with the chamber located both inside and outside the Mark II. Results on spatial resolution, average pulse shape, and some properties of CO{sub 2} mixtures are presented. 10 refs., 12 figs., 1 tab.

Alexander, J.P.; Baggs, R.; Fujino, D.; Hayes, K.; Hoard, C.; Hower, N.; Hutchinson, D.; Jaros, J.A.; Koetke, D.; Kowalski, L.A.

1989-03-01T23:59:59.000Z

373

Mark Henson | Photosynthetic Antenna Research Center  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: VegetationEquipment Surfaces andMapping the Nanoscale Landscape Print For3MarinaDepartmentMark H.Mark

374

Community Development Department Building & Safety Division  

E-Print Network [OSTI]

BUILDING, RESIDENTIAL AND GREEN BUILDING CODES, AMENDING FREMONT MUNICIPAL CODE TITLE vn (BUILDING TO ENERGY REGULATIONS THE 2010 CALIFORNIA,GREEN BUILDING CODE The City of Fremont proposed to adopt local................ Community Development Department Building & Safety Division 39550 Liberty Street

375

EARTH SCIENCES DIVISION ANNUAL REPORT 1978  

E-Print Network [OSTI]

of electrolytes: IX, rare earth chlorides, nitrates, andU E OF AQUIFER RESPONSE TO EARTH TIDES AS A MEANS O F SLawrence Berkeley Laboratory, Earth Sciences Division, 1977.

Authors, Various

2012-01-01T23:59:59.000Z

376

Financial Services Division of Administration & Finance  

E-Print Network [OSTI]

Financial Services Division of Administration & Finance (657) 278-2512 / Fax (714) 278: May Wong / Financial Services (CP-300). Instructions are at Questions? Email Directive11@fullerton.eduwww.finance

de Lijser, Peter

377

INDIVIDUAL DISCIPLINES: HUMAN RESOURCES DIVISION MARKETING  

E-Print Network [OSTI]

INDIVIDUAL DISCIPLINES: HUMAN RESOURCES DIVISION MARKETING AND RECRUITMENT CAMPAIGN STAFF .:|:. Client: Y. Mankin, Computing Sciences #12;DESIGN MAIN MENU 1 2 344 4 5WEBSITES Joint BioEnergy Institute

378

EARTH SCIENCES DIVISION ANNUAL REPORT 1978  

E-Print Network [OSTI]

of Energy's Division of Geothermal Energy has undertaken aand Ghormley, E. L. , 1976. Geothermal energy conversion andi a , Mexico, i n Geothermal energy: a n o v e l t y becomes

Authors, Various

2012-01-01T23:59:59.000Z

379

Energy Research and Development Division STAFF REPORT  

E-Print Network [OSTI]

Energy Research and Development Division STAFF REPORT NATURAL GAS RESEARCH AND DEVELOPMENT 2013 Annual Report CALIFORNIA ENERGY COMMISSION Edmund G. Brown Jr., Governor OCTOBER 2013 CEC5002013111 #12; CALIFORNIA ENERGY COMMISSION Linda Schrupp Primary Authors Prepared for: California

380

Robert C. Holub Undergraduate Division Dean  

E-Print Network [OSTI]

less than coherent, consisting of a handful of interdisciplinary undergraduate programs (the UGIS part is the location of these various programs. The UGIS majors are located within the division (except in one case

Mofrad, Mohammad R. K.

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

ORNL/CON-224 Energy Division  

E-Print Network [OSTI]

ORNL/CON-224 Energy Division U.S. HEAT PUMP RESEARCH AND DEVELOPMENT PROJECTS 1976-1986 K. H ......................................... 2 3. ORGANIZATIONS SPONSORING HEAT PUMP ................. RESEARCH AND DEVELOPMENT ............................................... 223 9. NOVEL HEAT PUMP CYCLES ............ ........................... 228 10. CROSSCUTTING PROJECTS

Oak Ridge National Laboratory

382

Materials Sciences Division Integrated Safety Management Plan  

E-Print Network [OSTI]

Materials Sciences Division Integrated Safety Management Plan Revised: February 9, 2012 Prepared by: signed Feb. 9, 2012 Rick Kelly, Facility/EH&S Manager Submitted by: signed Feb. 9, 2012 Miquel Salmeron.1 RESPONSIBILITY AND AUTHORITY THROUGH LINE MANAGEMENT............................................................5

383

Earth Sciences Division annual report 1989  

SciTech Connect (OSTI)

This Annual Report presents summaries of selected representative research activities from Lawrence Berkeley Laboratory grouped according to the principal disciplines of the Earth Sciences Division: Reservoir Engineering and Hydrology, Geology and Geochemistry, and Geophysics and Geomechanics. We are proud to be able to bring you this report, which we hope will convey not only a description of the Division's scientific activities but also a sense of the enthusiasm and excitement present today in the Earth Sciences.

Not Available

1990-06-01T23:59:59.000Z

384

Weapons Experiments Division Explosives Operations Overview  

SciTech Connect (OSTI)

Presentation covers WX Division programmatic operations with a focus on JOWOG-9 interests. A brief look at DARHT is followed by a high level overview of explosives research activities currently being conducted within in the experimental groups of WX-Division. Presentation covers more emphasis of activities and facilities at TA-9 as these efforts have been more traditionally aligned with ongoing collaborative explosive exchanges covered under JOWOG-9.

Laintz, Kenneth E. [Los Alamos National Laboratory

2012-06-19T23:59:59.000Z

385

NO. REV. NO. Systems Division DATE  

E-Print Network [OSTI]

-~ NO. REV. NO. EATM-15 PAGE OF ~ Systems Division DATE EASEP /PSEP Solar Panel Development Design+"'--.:L'_;;;J....;::::::..··-=·~::!!:!!!e::...._ K. Hsi #12;NO. REV. NO. EATM-15 EASEP/PSEP Solar Panel Development ~ Systems Division Design of the EASE-PSEP Solar Panel Array~PA::G:,:E:..::=l=~o:F~=2=7= DATE 20 Nov. 1968 1. 0 SUMMARY Electrical power

Rathbun, Julie A.

386

Earth Sciences Division collected abstracts: 1980  

SciTech Connect (OSTI)

This report is a compilation of abstracts of papers, reports, and talks presented during 1980 at national and international meetings by members of the Earth Sciences Division, Lawrence Livermore National Laboratory. The arrangement is alphabetical (by author). For a given report, a bibliographic reference appears under the name of each coauthor, but the abstract itself is given only under the name of the first author (indicated in capital letters) or the first Earth Sciences Division author.

Henry, A.L.; Hornady, B.F. (eds.)

1981-10-15T23:59:59.000Z

387

Organization of ISI by Divisions and Constituent Units Information Sciences Division  

E-Print Network [OSTI]

Biological Sciences Division Agricultural and Ecological Research Unit Human Genetics Unit Biological Unit Canteen Security Unit Medical Welfare Unit Telephone Unit Transport Unit Guest House Audio Visual

Bandyopadhyay, Antar

388

UNIVERSITY OF CALIFORNIA, SANTA CRUZ DIVISION OF GRADUATE STUDIES  

E-Print Network [OSTI]

and Graduate Division coordination of efforts to increase graduate support and postdoctoral placement through

California at Santa Cruz, University of

389

State-of-the art of freight forecast modeling: lessons learned and the road ahead  

E-Print Network [OSTI]

of-the art of freight forecast modeling: lessons learned andof goods as well as to forecast the expected future truckused for the short-term forecasts of freight volumes on

Chow, Joseph Y.; Yang, Choon Heon; Regan, Amelia C.

2010-01-01T23:59:59.000Z

390

Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices  

E-Print Network [OSTI]

revisions to the EIAs natural gas price forecasts in AEOsolely on the AEO 2005 natural gas price forecasts willComparison of AEO 2005 Natural Gas Price Forecast to NYMEX

Bolinger, Mark; Wiser, Ryan

2004-01-01T23:59:59.000Z

391

Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices  

E-Print Network [OSTI]

to estimate the base-case natural gas price forecast, but toComparison of AEO 2010 Natural Gas Price Forecast to NYMEXs reference-case long-term natural gas price forecasts from

Bolinger, Mark A.

2010-01-01T23:59:59.000Z

392

Electricity Demand Forecasting using Gaussian Processes Manuel Blum and Martin Riedmiller  

E-Print Network [OSTI]

Electricity Demand Forecasting using Gaussian Processes Manuel Blum and Martin Riedmiller Abstract We present an electricity demand forecasting algorithm based on Gaussian processes. By introducing. Introduction Electricity demand forecasting is an important aspect of the control and scheduling of power

Teschner, Matthias

393

Reducing the demand forecast error due to the bullwhip effect in the computer processor industry  

E-Print Network [OSTI]

Intel's current demand-forecasting processes rely on customers' demand forecasts. Customers do not revise demand forecasts as demand decreases until the last minute. Intel's current demand models provide little guidance ...

Smith, Emily (Emily C.)

2010-01-01T23:59:59.000Z

394

Evaluation of forecasting techniques for short-term demand of air transportation  

E-Print Network [OSTI]

Forecasting is arguably the most critical component of airline management. Essentially, airlines forecast demand to plan the supply of services to respond to that demand. Forecasts of short-term demand facilitate tactical ...

Wickham, Richard Robert

1995-01-01T23:59:59.000Z

395

MACDONALD POLYNOMIALS AND GEOMETRY MARK HAIMAN  

E-Print Network [OSTI]

MACDONALD POLYNOMIALS AND GEOMETRY MARK HAIMAN Contents 1. Introduction 2. Symmetric functions and Macdonald polynomials 3. The n! conjecture 4. The Hilbert scheme and Xn 5. Frobenius series 6. The ideals J by Macdonald [26], and the geometry of certain algebraic varieties, notably the Hilbert scheme Hilbn (C2

Haiman, Mark D.

396

MACDONALD POLYNOMIALS AND GEOMETRY MARK HAIMAN  

E-Print Network [OSTI]

MACDONALD POLYNOMIALS AND GEOMETRY MARK HAIMAN Contents 1. Introduction 2. Symmetric functions and Macdonald polynomials 3. The n! conjecture 4. The Hilbert scheme and X n 5. Frobenius series 6. The ideals J by Macdonald [26], and the geometry of certain algebraic varieties, notably the Hilbert scheme Hilb n (C 2

Haiman, Mark D.

397

Computing Valuation Popov Forms Mark Giesbrecht1  

E-Print Network [OSTI]

Computing Valuation Popov Forms Mark Giesbrecht1 , George Labahn1 , and Yang Zhang2 1 School. Popov forms and weak Popov forms of matrices over non- commutative valuation domains are defined rings. In the computer alge- bra area, Abramov and Bronstein [1] gave a method to calculate the ranks

Labahn, George

398

Programming Environments for Novices Mark Guzdial  

E-Print Network [OSTI]

Programming Environments for Novices Mark Guzdial College of Computing, Georgia Institute of Technology guzdial@cc.gatech.edu May 7, 2003 1 Specializing Environments for Novices The task of specializing programming environments for novices begins with the recog- nition that programming is a hard skill to learn

Guzdial, Mark

399

A Web Site Navigation Engine Mark Levene  

E-Print Network [OSTI]

A Web Site Navigation Engine Mark Levene Department of Computer Science Birkbeck College site-specific search engines is that they are not able to pick up the "scent of information" [5 is looking for. Moreover, Hearst [2] argues that next gener- ation site-specific search engines should

Levene, Mark

400

Variational Gaussian Process Classifiers Mark N. Gibbs  

E-Print Network [OSTI]

Variational Gaussian Process Classifiers Mark N. Gibbs Cavendish Laboratory Cambridge CB3 0HE United Kingdom David J.C. MacKay \\Lambda Cavendish Laboratory Cambridge CB3 0HE United Kingdom Submitted­linear interpolation tool (Williams 1995; Williams and Rasmussen 1996), but it is not straightforward to solve

MacKay, David J.C.

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

, Mark Johnson1 , Wu Meng Tan1  

E-Print Network [OSTI]

Paul Pace1 , Mark Johnson1 , Wu Meng Tan1 , Georgina Mosedale1 , Chelvin Sng1 , Maureen Hoatlin2@mrc-lmb.cam.ac.uk P.Pace and M.Johnson contributed equally to this work The Fanconi anaemia (FA) nuclear complex (com

Patel, KJ

402

School Of Architecture Mark Robbins, Dean  

E-Print Network [OSTI]

School Of Architecture Mark Robbins, Dean 201 Slocum Hall soa.syr.edu About The College Dean's Message Architecture is a complex discipline that organizes diverse human needs and interests, ranging from the pragmatic to the visionary. Syracuse Architecture offers a professional education rooted

McConnell, Terry

403

3 445b 0377240 2 Mark Elless  

E-Print Network [OSTI]

Integrated Demonstration Program coordinated by Kim Nuhfer, Fernald Environmental Restoration Management-term equilibration study involvingtwo uranium-contaminated soils at the Department of Energy's Fernald Environmental_ ........ ~ .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . -~ .. ~~ _ ......... --- #12;Solubility Measurement of Uranium in Uranium-Contaminated Soils S . Y.Lee, Mark Elless

Hoffman, Forrest M.

404

Wind Forecasting Improvement Project | Department of Energy  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOf TheViolations | Department of EnergyisWilliamForecasting

405

Renewable Forecast Min-Max2020.xls  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared at 278, 298,NIST31 ORV 15051SoilWind Energy Wind RenewableForecast

406

Forecast calls for better models | EMSL  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickr Flickr Editor's note: Since theNational SupplementalFor theForecast

407

NREL: Resource Assessment and Forecasting - Facilities  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and Resources NREL resource assessment and forecasting

408

NREL: Resource Assessment and Forecasting - Research Staff  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions andData and Resources NREL resource assessment and forecastingResearch

409

Section III, Division 5 - Development And Future Directions  

SciTech Connect (OSTI)

This paper provides commentary on a new division under Section III of the ASME Boiler and Pressure Vessel (BPV) Code. This new Division 5 has an issuance date of November 1, 2011 and is part of the 2011 Addenda to the 2010 Edition of the BPV Code. The new Division covers the rules for the design, fabrication, inspection and testing of components for high temperature nuclear reactors. Information is provided on the scope and need for Division 5, the structure of Division 5, where the rules originated, the various changes made in finalizing Division 5, and the future near-term and long-term expectations for Division 5 development.

Morton, Dana K. [Idaho National Laboratory (INL)] [Idaho National Laboratory (INL); Jetter, Robert I [Consultant] [Consultant; Nestell, James E. [MPR Associates Inc.] [MPR Associates Inc.; Burchell, Timothy D [ORNL] [ORNL; Sham, Sam [ORNL] [ORNL

2012-01-01T23:59:59.000Z

410

Progress Report on Power Division Work Plan  

E-Print Network [OSTI]

technologies Data development for the WECC/TEPPC 2020 transmission assessment 7 #12;Bonneville Resource of adequacy methodology Work with WECC and NERC on assessments 9 #12;Demand Response & Smart Grid Review Participation in WECC Transmission Expansion Planning Policy Committee (TEPPC) Provided PNW load forecast

411

Biology Division progress report, October 1, 1991--September 30, 1993  

SciTech Connect (OSTI)

This Progress Report summarizes the research endeavors of the Biology Division of the Oak Ridge National Laboratory during the period October 1, 1991, through September 30, 1993. The report is structured to provide descriptions of current activities and accomplishments in each of the Division`s major organizational units. Lists of information to convey the entire scope of the Division`s activities are compiled at the end of the report.

Hartman, F.C.; Cook, J.S.

1993-10-01T23:59:59.000Z

412

MarkPearce-KTHStockholm-Stockholm Skolors Kosmiska Ntverk  

E-Print Network [OSTI]

antenna Sensors Pressure sensor GPS receiver MarkPearce-KTHStockholm- #12;MarkPearce-KTHStockholm- t(GPS 1) t(GPS 2) [ns] t(GPS1)t(GPS2)[ns] Trigger no. #12;MarkPearce-KTHStockholm- Photo: P. Walck #12;Mark

Haviland, David

413

Fast Facts Office of Public Affairs, 314-935-5230 Mark S. Wrighton, Ph.D.  

E-Print Network [OSTI]

Division III colleges · Labeled as a "powerhouse" in Division III by The New York Times · Founding member

414

Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty  

E-Print Network [OSTI]

114 Solar Irradiance And Power Output Variabilityand L. Bangyin. Online 24-h solar power forecasting based onNielsen. Online short-term solar power forecasting. Solar

Marquez, Ricardo

2012-01-01T23:59:59.000Z

415

Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast  

E-Print Network [OSTI]

Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast ................................................................................................. 2 Economic Drivers of Residential Demand

416

Improving baseline forecasts in a 500-industry dynamic CGE model of the USA.  

E-Print Network [OSTI]

??MONASH-style CGE models have been used to generate baseline forecasts illustrating how an economy is likely to evolve through time. One application of such forecasts (more)

Mavromatis, Peter George

2013-01-01T23:59:59.000Z

417

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA  

SciTech Connect (OSTI)

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing quasi-deterministic components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27T23:59:59.000Z

418

Distribution Based Data Filtering for Financial Time Series Forecasting  

E-Print Network [OSTI]

recent past. In this paper, we address the challenge of forecasting the behavior of time series using@unimelb.edu.au Abstract. Changes in the distribution of financial time series, particularly stock market prices, can of stock prices, which aims to forecast the future values of the price of a stock, in order to obtain

Bailey, James

419

On the reliability of seasonal forecasts Antje Weisheimer  

E-Print Network [OSTI]

On the reliability of seasonal forecasts Antje Weisheimer Weisheimer to achieving a "5"? à Use reliability of non-climatological forecastsDon: · if (X) C(X) à climatological (reliable) informaDon · if (X) C(X) à

Stevenson, Paul

420

SATELLITE BASED SHORT-TERM FORECASTING OF SOLAR IRRADANCE  

E-Print Network [OSTI]

SATELLITE BASED SHORT-TERM FORECASTING OF SOLAR IRRADANCE - COMPARISON OF METHODS AND ERROR Forecasting of solar irradiance will become a major issue in the future integration of solar energy resources method was used to derive motion vector fields from two consecutive images. The future image

Heinemann, Detlev

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Predicting Solar Generation from Weather Forecasts Using Machine Learning  

E-Print Network [OSTI]

of smart grid initiatives is significantly increasing the fraction of grid energy contributed by renewables existing forecast-based models. I. INTRODUCTION A key goal of smart grid efforts is to substantially-based prediction models built using seven distinct weather forecast metrics are 27% more accurate for our site than

Shenoy, Prashant

422

Forecasting Uncertainty Related to Ramps of Wind Power Production  

E-Print Network [OSTI]

- namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

Boyer, Edmond

423

FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS  

E-Print Network [OSTI]

FORECASTING WATER DEMAND USING CLUSTER AND REGRESSION ANALYSIS by Bruce Bishop Professor of Civil resources resulting in water stress. Effective water management ­ a solution Supply side management Demand side management #12;Developing a regression equation based on cluster analysis for forecasting water

Keller, Arturo A.

424

Revised 1997 Retail Electricity Price Forecast Principal Author: Ben Arikawa  

E-Print Network [OSTI]

Revised 1997 Retail Electricity Price Forecast March 1998 Principal Author: Ben Arikawa Electricity 1997 FORE08.DOC Page 1 CALIFORNIA ENERGY COMMISSION ELECTRICITY ANALYSIS OFFICE REVISED 1997 RETAIL ELECTRICITY PRICE FORECAST Introduction The Electricity Analysis Office of the California Energy Commission

425

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

426

Impact of PV forecasts uncertainty in batteries management in microgrids  

E-Print Network [OSTI]

-- Photovoltaic systems, Batteries, Forecasting I. INTRODUCTION This paper presents first results of a study Energies and Energy Systems Sophia Antipolis, France andrea.michiorri@mines-paristech.fr Abstract production forecast algorithm is used in combination with a battery schedule optimisation algorithm. The size

Paris-Sud XI, Université de

427

Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging  

E-Print Network [OSTI]

distribution; Numerical weather prediction; Skewed distribution; Truncated data; Wind energy. 1. INTRODUCTION- native. Purely statistical methods have been applied to short-range forecasts for wind speed only a fewProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

Raftery, Adrian

428

Introducing the Canadian Crop Yield Forecaster Aston Chipanshi1  

E-Print Network [OSTI]

for crop yield forecasting and risk analysis. Using the Census Agriculture Region (CAR) as the unit Climate Decision Support and Adaptation, Agriculture and Agri-Food Canada, 1011, Innovation Blvd, Saskatoon, SK S7V 1B7, Canada The Canadian Crop Yield Forecaster (CCYF) is a statistical modelling tool

Miami, University of

429

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size  

E-Print Network [OSTI]

A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size Andrew. R.Lawrence@ecmwf.int #12;Abstract An ensemble-based data assimilation approach is used to transform old en- semble. The impact of the transformations are propagated for- ward in time over the ensemble's forecast period

Hansens, Jim

430

Forecasting Building Occupancy Using Sensor Network James Howard  

E-Print Network [OSTI]

of the forecasting algorithm for the different conditions. 1. INTRODUCTION According to the U.S. Department of Energy could take advantage of times when electricity cost is lower, to chill a cold water storage tankForecasting Building Occupancy Using Sensor Network Data James Howard Colorado School of Mines

Hoff, William A.

431

Energy Technology Division research summary - 1999.  

SciTech Connect (OSTI)

The Energy Technology Division provides materials and engineering technology support to a wide range of programs important to the US Department of Energy. As shown on the preceding page, the Division is organized into ten sections, five with concentrations in the materials area and five in engineering technology. Materials expertise includes fabrication, mechanical properties, corrosion, friction and lubrication, and irradiation effects. Our major engineering strengths are in heat and mass flow, sensors and instrumentation, nondestructive testing, transportation, and electromechanics and superconductivity applications. The Division Safety Coordinator, Environmental Compliance Officers, Quality Assurance Representative, Financial Administrator, and Communication Coordinator report directly to the Division Director. The Division Director is personally responsible for cultural diversity and is a member of the Laboratory-wide Cultural Diversity Advisory Committee. The Division's capabilities are generally applied to issues associated with energy production, transportation, utilization, or conservation, or with environmental issues linked to energy. As shown in the organization chart on the next page, the Division reports administratively to the Associate Laboratory Director (ALD) for Energy and Environmental Science and Technology (EEST) through the General Manager for Environmental and Industrial Technologies. While most of our programs are under the purview of the EEST ALD, we also have had programs funded under every one of the ALDs. Some of our research in superconductivity is funded through the Physical Research Program ALD. We also continue to work on a number of nuclear-energy-related programs under the ALD for Engineering Research. Detailed descriptions of our programs on a section-by-section basis are provided in the remainder of this book.

NONE

1999-03-31T23:59:59.000Z

432

Voluntary Green Power Market Forecast through 2015  

SciTech Connect (OSTI)

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

433

Electrical Inspection in the PHYSICS Division  

E-Print Network [OSTI]

recognized Nationally Recognized Testing Laboratory (NRTL) do not need to be inspected. Examples Technologies). #12;4 Examples of NRTL Markings #12;5 Equipment Considered Non-hazardous For 60 Hz AC, has no identified markings from any of the NRTL labs appearing on the OSHA list, the equipment

Kemner, Ken

434

Transportation Energy Technology DivisionEnergy Technology Division --TribologyTribology  

E-Print Network [OSTI]

-frictionless carbon coatings to the components when appropriate · Develop and evaluate polymer composite materials to their prototype using Hitco C/C composite and anodized aluminum material combination. · Fabricated and evaluatedTransportation Materials Energy Technology DivisionEnergy Technology Division -- Tribology

435

Division of Student Life 20122013 ANNUAL REPORT Division of Student Life  

E-Print Network [OSTI]

1 Division of Student Life 20122013 ANNUAL REPORT Division of Student Life #12;2 The Power to Transform: Expectations of Our Students At UWMadison, we know that the Wisconsin Experience has learning inside and outside the classroom to make the world a better place?" In the eight departments

436

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint  

SciTech Connect (OSTI)

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

2012-07-01T23:59:59.000Z

437

Verification of hourly forecasts of wind turbine power output  

SciTech Connect (OSTI)

A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

Wegley, H.L.

1984-08-01T23:59:59.000Z

438

Nuclear Chemistry Division annual report FY83  

SciTech Connect (OSTI)

The purpose of the annual reports of the Nuclear Chemistry Division is to provide a timely summary of research activities pursued by members of the Division during the preceding year. Throughout, details are kept to a minimum; readers desiring additional information are encouraged to read the referenced documents or contact the authors. The Introduction presents an overview of the Division's scientific and technical programs. Next is a section of short articles describing recent upgrades of the Division's major facilities, followed by sections highlighting scientific and technical advances. These are grouped under the following sections: nuclear explosives diagnostics; geochemistry and environmental sciences; safeguards technology and radiation effect; and supporting fundamental science. A brief overview introduces each section. Reports on research supported by a particular program are generally grouped together in the same section. The last section lists the scientific, administrative, and technical staff in the Division, along with visitors, consultants, and postdoctoral fellows. It also contains a list of recent publications and presentations. Some contributions to the annual report are classified and only their abstracts are included in this unclassified portion of the report (UCAR-10062-83/1); the full article appears in the classified portion (UCAR-10062-83/2).

Struble, G. (ed.)

1983-01-01T23:59:59.000Z

439

Energy Technology Division research summary -- 1994  

SciTech Connect (OSTI)

Research funded primarily by the NRC is directed toward assessing the roles of cyclic fatigue, intergranular stress corrosion cracking, and irradiation-assisted stress corrosion cracking on failures in light water reactor (LWR) piping systems, pressure vessels, and various core components. In support of the fast reactor program, the Division has responsibility for fuel-performance modeling and irradiation testing. The Division has major responsibilities in several design areas of the proposed International Thermonuclear Experimental Reactor (ITER). The Division supports the DOE in ensuring safe shipment of nuclear materials by providing extensive review of the Safety Analysis Reports for Packaging (SARPs). Finally, in the nuclear area they are investigating the safe disposal of spent fuel and waste. In work funded by DOE`s Energy Efficiency and Renewable Energy, the high-temperature superconductivity program continues to be a major focal point for industrial interactions. Coatings and lubricants developed in the division`s Tribology Section are intended for use in transportation systems of the future. Continuous fiber ceramic composites are being developed for high-performance heat engines. Nondestructive testing techniques are being developed to evaluate fiber distribution and to detect flaws. A wide variety of coatings for corrosion protection of metal alloys are being studied. These can increase lifetimes significant in a wide variety of coal combustion and gasification environments.

Not Available

1994-09-01T23:59:59.000Z

440

NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts  

E-Print Network [OSTI]

· NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt Global Insight, paid for by the West Virginia Department of Revenue. 2013 WEST VIRGINIA ECONOMIC OUTLOOKWest Virginia Economic Outlook 2013 is published by: Bureau of Business & Economic Research West

Mohaghegh, Shahab

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Identification marking by means of laser peening  

DOE Patents [OSTI]

The invention is a method and apparatus for marking components by inducing a shock wave on the surface that results in an indented (strained) layer and a residual compressive stress in the surface layer. One embodiment of the laser peenmarking system rapidly imprints, with single laser pulses, a complete identification code or three-dimensional pattern and leaves the surface in a state of deep residual compressive stress. A state of compressive stress in parts made of metal or other materials is highly desirable to make them resistant to fatigue failure and stress corrosion cracking. This process employs a laser peening system and beam spatial modulation hardware or imaging technology that can be setup to impress full three dimensional patterns into metal surfaces at the pulse rate of the laser, a rate that is at least an order of magnitude faster than competing marking technologies.

Hackel, Lloyd A. (Livermore, CA); Dane, C. Brent (Livermore, CA); Harris, Fritz (Rocklin, CA)

2002-01-01T23:59:59.000Z

442

Chemical Technology Division annual technical report, 1996  

SciTech Connect (OSTI)

CMT is a diverse technical organization with principal emphases in environmental management and development of advanced energy sources. It conducts R&D in 3 general areas: development of advanced power sources for stationary and transportation applications and for consumer electronics, management of high-level and low-level nuclear wastes and hazardous wastes, and electrometallurgical treatment of spent nuclear fuel. The Division also performs basic research in catalytic chemistry involving molecular energy resources, mechanisms of ion transport in lithium battery electrolytes, materials chemistry of electrified interfaces and molecular sieves, and the theory of materials properties. It also operates the Analytical Chemistry Laboratory, which conducts research in analytical chemistry and provides analytical services for programs at ANL and other organizations. Technical highlights of the Division`s activities during 1996 are presented.

NONE

1997-06-01T23:59:59.000Z

443

Life Sciences Division annual report, 1988  

SciTech Connect (OSTI)

This report summarizes the research and development activities of Los Alamos National Laboratory's Life Sciences Division for the calendar year 1988. Technical reports related to the current status of projects are presented in sufficient detail to permit the informed reader to assess their scope and significance. Summaries useful to the casual reader desiring general information have been prepared by the Group Leaders and appear in each group overview. Investigators on the staff of the Life Sciences Division will be pleased to provide further information.

Marrone, B.L.; Cram, L.S. (comps.)

1989-04-01T23:59:59.000Z

444

A Cosmology Forecast Toolkit -- CosmoLib  

E-Print Network [OSTI]

The package CosmoLib is a combination of a cosmological Boltzmann code and a simulation toolkit to forecast the constraints on cosmological parameters from future observations. In this paper we describe the released linear-order part of the package. We discuss the stability and performance of the Boltzmann code. This is written in Newtonian gauge and including dark energy perturbations. In CosmoLib the integrator that computes the CMB angular power spectrum is optimized for a $\\ell$-by-$\\ell$ brute-force integration, which is useful for studying inflationary models predicting sharp features in the primordial power spectrum of metric fluctuations. The numerical code and its documentation are available at http://www.cita.utoronto.ca/~zqhuang/CosmoLib.

Zhiqi Huang

2012-06-11T23:59:59.000Z

445

Incorporating Forecast Uncertainty in Utility Control Center  

SciTech Connect (OSTI)

Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian

2014-07-09T23:59:59.000Z

446

Development and testing of improved statistical wind power forecasting methods.  

SciTech Connect (OSTI)

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-12-06T23:59:59.000Z

447

DOE FESAC Chair Mark Koepke Presents Special Seminar, 'Partnering...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

capabilities at the interface of astronomical observations and laboratory-based plasma research. Koepke has served as chair of the American Physical Society (APS) Division of...

448

Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty  

E-Print Network [OSTI]

Solar irradiance data . . . . . . . . . . . . .Accuracy . . . . . . . . . . . . . . . . . Solar Resourcev Uncertainty In Solar Resource: Forecasting

Marquez, Ricardo

2012-01-01T23:59:59.000Z

449

Documentation of the Hourly Time Series NCEP Climate Forecast System Reanalysis  

E-Print Network [OSTI]

- 1 - Documentation of the Hourly Time Series from the NCEP Climate Forecast System Reanalysis: ------------------------------------------------------------------------------------------------------------ Initial condition 1 Jan 1979, 0Z Record 1: f00: forecast at first time step of 3 mins Record 2: f01: forecast (either averaged over 0 to 1 hour, or instantaneous at 1 hour) Record 3: f02: forecast (either

450

Solving the problem of inadequate scoring rules for assessing probabilistic football forecast models  

E-Print Network [OSTI]

Solving the problem of inadequate scoring rules for assessing probabilistic football forecast forecasting models, and the relative simplicity of the outcome of such forecasts (they require only three their forecast accuracy. Moreover, the various scoring rules used for validation in previous studies

Fenton, Norman

451

Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast System  

E-Print Network [OSTI]

Development, implementation, and skill assessment of the NOAA/NOS Great Lakes Operational Forecast Lakes Operational Forecast System (GLOFS) uses near-real-time atmospheric observa- tions and numerical weather prediction forecast guidance to produce three-dimensional forecasts of water temperature

452

Ozone ensemble forecast with machine learning Vivien Mallet,1,2  

E-Print Network [OSTI]

Ozone ensemble forecast with machine learning algorithms Vivien Mallet,1,2 Gilles Stoltz,3 forecasts. The latter rely on a multimodel ensemble built for ozone forecasting with the modeling system Europe in order to forecast ozone daily peaks and ozone hourly concentrations. On the basis of past

Paris-Sud XI, Université de

453

MLWFA: A Multilingual Weather Forecast Text Generation Tianfang YAO Dongmo ZHANG Qian WANG  

E-Print Network [OSTI]

MLWFA: A Multilingual Weather Forecast Text Generation System1 Tianfang YAO Dongmo ZHANG Qian WANG generation; Weather forecast generation system Abstract In this demonstration, we present a system for multilingual text generation in the weather forecast domain. Multilingual Weather Forecast Assistant (MLWFA

Wu, Dekai

454

November 14, 2000 A Quarterly Forecast of U.S. Trade  

E-Print Network [OSTI]

November 14, 2000 A Quarterly Forecast of U.S. Trade in Services and the Current Account, 2000 of Forecast*** We forecast that the services trade surplus, which declined from 1997 to 1998 and edged upward. That is, from a level of $80.6 billion in 1999, we forecast that the services trade surplus will be $80

Shyy, Wei

455

USING BOX-JENKINS MODELS TO FORECAST FISHERY DYNAMICS: IDENTIFICATION, ESTIMATION, AND CHECKING  

E-Print Network [OSTI]

~ is illustrated by developing a model that makes monthly forecasts of skipjack tuna, Katsuwonus pelamis, catches

456

Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)  

SciTech Connect (OSTI)

Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

Lantz, E.; Hand, M.

2010-05-01T23:59:59.000Z

457

ASSESSING THE QUALITY AND ECONOMIC VALUE OF WEATHER AND CLIMATE FORECASTS  

E-Print Network [OSTI]

INFORMATION SYSTEM Forecast -- Conditional probability distribution for event Z = z indicates forecast tornado #12;(1.2) FRAMEWORK Joint Distribution of Observations & Forecasts Observed Weather = Forecast probability p (e.g., induced by Z) Reliability Diagram Observed weather: = 1 (Adverse weather occurs) = 0

Katz, Richard

458

A comparison of univariate methods for forecasting electricity demand up to a day ahead  

E-Print Network [OSTI]

A comparison of univariate methods for forecasting electricity demand up to a day ahead James W methods for short-term electricity demand forecasting for lead times up to a day ahead. The very short of Forecasters. Published by Elsevier B.V. All rights reserved. Keywords: Electricity demand forecasting

McSharry, Patrick E.

459

Resource Adequacy Load Forecast A Report to the Resource Adequacy Advisory Committee  

E-Print Network [OSTI]

one hour peak demand and monthly energy assuming normal weather. The Council forecast includes loadsResource Adequacy Load Forecast A Report to the Resource Adequacy Advisory Committee Tomás of the assessment is the load forecast. The Council staff has recently developed a load forecast to be used

460

A collaborative demand forecasting process with event-based fuzzy judgements Naoufel Cheikhrouhou a,  

E-Print Network [OSTI]

A collaborative demand forecasting process with event-based fuzzy judgements Naoufel Cheikhrouhou a July 2011 Keywords: Collaborative forecasting Demand planning Judgement Time series Fuzzy logic a b s t r a c t Mathematical forecasting approaches can lead to reliable demand forecast in some

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Demand forecast accuracy and performance of inventory policies under multi-level rolling  

E-Print Network [OSTI]

Demand forecast accuracy and performance of inventory policies under multi-level rolling schedule is to study the behaviour of lot-sizing rules in a multi- level context when forecast demand is subject Interchange to ameliorate demand forecast. Although the presence or absence of forecast errors matters more

Paris-Sud XI, Université de

462

Evaluation of copper for divider subassembly in MCO Mark IA and Mark IV scrap fuel baskets  

SciTech Connect (OSTI)

The K Basin Spent Nuclear Fuel (SNF) Project Multi-Canister Overpack (MCO) subprojection eludes the design and fabrication of a canister that will be used to confine, contain, and maintain fuel in a critically safe array to enable its removal from the K Basins, vacuum drying, transport, staging, hot conditioning, and interim storage (Goldinann 1997). Each MCO consists of a shell, shield plug, fuel baskets (Mark IA or Mark IV), and other incidental equipment. The Mark IA intact and scrap fuel baskets are a safety class item for criticality control and components necessary for criticality control will be constructed from 304L stainless steel. It is proposed that a copper divider subassembly be used in both Mark IA and Mark IV scrap baskets to increase the safety basis margin during cold vacuum drying. The use of copper would increase the heat conducted away from hot areas in the baskets out to the wall of the MCO by both radiative and conductive heat transfer means. Thus copper subassembly will likely be a safety significant component of the scrap fuel baskets. This report examines the structural, cost and corrosion consequences associated with using a copper subassembly in the stainless steel MCO scrap fuel baskets.

Graves, C.E.

1997-09-29T23:59:59.000Z

463

Hilton Alexandria Mark Center Shuttle Schedule  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarly Career Scientists'Montana.ProgramJulietip sheetK-4In 2013 many| DepartmentAndreaHilton Alexandria Mark

464

Mark D. Mitchell | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen OwnedofDepartment ofJared Temanson -ofMarc Morial - PresidentEnergyMark D.

465

SolidMarks | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:Seadov Pty Ltd Jump to:InformationSolergy Power Jump to:SolidMarks Jump to:

466

Mark Hereld | Argonne Leadership Computing Facility  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fund LasDubey selected asMarat Valiev30 MarchARMMarkMark

467

Mark Vermilyea | Inventors | GE Global Research  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recovery challenge fund LasDubey selected asMarat Valiev30R Fahey DirectorMark

468

Physics Division activities report, 1986--1987  

SciTech Connect (OSTI)

This report summarizes the research activities of the Physics Division for the years 1986 and 1987. Areas of research discussed in this paper are: research on e/sup +/e/sup /minus// interactions; research on p/bar p/ interactions; experiment at TRIUMF; double beta decay; high energy astrophysics; interdisciplinary research; and advanced technology development and the SSC.

Not Available

1987-01-01T23:59:59.000Z

469

Division of Human Resources Termination Of  

E-Print Network [OSTI]

Division of Human Resources Termination Of Domestic Partnership Health Stipend Questions (813) 974 Insurance Stipend will terminate as of the Effective Date on this Termination of Domestic Partnership Health. ______ The Domestic Partnership Declaration attested to and filed by me with USF shall be and is terminated

Meyers, Steven D.

470

ENVIRONMENT, SAFETY, HEALTH, AND QUALITY DIVISION  

E-Print Network [OSTI]

for its scope of work (the prime prepares a site-specific safety plan content and approval form for each Subcontractor Safety: Non-green Work Procedure [SLAC-I-730-0A21C-024].) Project Name PR # SLAC Project ContactsENVIRONMENT, SAFETY, HEALTH, AND QUALITY DIVISION Chapter 42: Subcontractor Safety Site

Wechsler, Risa H.

471

Division of Human Resources Nonresident Alien Federal  

E-Print Network [OSTI]

Division of Human Resources Nonresident Alien Federal Withholding Requirements Questions (813) 974 classified as nonresident aliens for tax purposes with regard to their federal withholding taxes.gov. In brief, the Form W-4 requirements for individuals who are nonresident aliens (NRA) for tax purposes

Meyers, Steven D.

472

Earth Sciences Division annual report 1990  

SciTech Connect (OSTI)

This Annual Report presents summaries of selected representative research activities grouped according to the principal disciplines of the Earth Sciences Division: Reservoir Engineering and Hydrogeology, Geology and Geochemistry, and Geophysics and Geomechanics. Much of the Division`s research deals with the physical and chemical properties and processes in the earth`s crust, from the partially saturated, low-temperature near-surface environment to the high-temperature environments characteristic of regions where magmatic-hydrothermal processes are active. Strengths in laboratory and field instrumentation, numerical modeling, and in situ measurement allow study of the transport of mass and heat through geologic media -- studies that now include the appropriate chemical reactions and the hydraulic-mechanical complexities of fractured rock systems. Of particular note are three major Division efforts addressing problems in the discovery and recovery of petroleum, the application of isotope geochemistry to the study of geodynamic processes and earth history, and the development of borehole methods for high-resolution imaging of the subsurface using seismic and electromagnetic waves. In 1989 a major DOE-wide effort was launched in the areas of Environmental Restoration and Waste Management. Many of the methods previously developed for and applied to deeper regions of the earth will in the coming years be turned toward process definition and characterization of the very shallow subsurface, where man-induced contaminants now intrude and where remedial action is required.

NONE

1991-06-01T23:59:59.000Z

473

DIVISION OF RECREATIONAL SPORTS Personal Training  

E-Print Network [OSTI]

Information Personal Training Policies Waiver Client Data Questionnaire Health Status Questionnaire PersonalDIVISION OF RECREATIONAL SPORTS Personal Training New Client Packet Personal Training Package to Purdue Rec Sports Personal Training Getting Started The information included in this packet is everything

Pittendrigh, Barry

474

Political Science Division Hatfield School of Government  

E-Print Network [OSTI]

Political Science Division Hatfield School of Government Minor in Law & Legal Studies Program, emphasizing the political, social, cultural, and philosophical foundations and impacts of law and legal campus who are interested in the relationship of law to politics, society, and culture. While the core

Bertini, Robert L.

475

Lectures on Linear Algebra over Division Ring  

E-Print Network [OSTI]

In this book i treat linear algebra over division ring. A system of linear equations over a division ring has properties similar to properties of a system of linear equations over a field. However, noncommutativity of a product creates a new picture. Matrices allow two products linked by transpose. Biring is algebra which defines on the set two correlated structures of the ring. As in the commutative case, solutions of a system of linear equations build up right or left vector space depending on type of system. We study vector spaces together with the system of linear equations because their properties have a close relationship. As in a commutative case, the group of automorphisms of a vector space has a single transitive representation on a frame manifold. This gives us an opportunity to introduce passive and active representations. Studying a vector space over a division ring uncovers new details in the relationship between passive and active transformations, makes this picture clearer. Considering of twin representations of division ring in Abelian group leads to the concept of D vector space and their linear map. Based on polyadditive map I considered definition of tensor product of rings and tensor product of D vector spaces.

Aleks Kleyn

2014-10-11T23:59:59.000Z

476

Division of Student Affairs 107 Conklin North  

E-Print Network [OSTI]

A. Herman graduated from Bowling Green State University's College Student Personnel program in 1990, August 31st to the Office of the Division of Student Affairs, Bowling Green State University, Attn: Beth Bowling Green State University Shelli A. Herman graduated from Bowling Green State University's College

Moore, Paul A.

477

PHYSICS DIVISION ESH BULLETIN 2005-06  

E-Print Network [OSTI]

conducted by the operations staff. Maintenance is work done by the crafts. Work done by Users is considered, and Guests were allowed to conduct hands-on experimental work under the direct supervision of a trained: Work in the Physics Division is broadly categorized as operations, maintenance, and experimental work

478

Student Regulations and Procedures Academic Division  

E-Print Network [OSTI]

Student Regulations and Procedures Academic Division 2007/2008 11 Students Union Code information regarding their course, tuition fees, award ceremonies and other matters www.mmu.ac.uk/academic's Articles of Government (Article 1.1). As prescribed in the Articles of Government (Article 12

479

Student Regulations and Procedures Academic Division  

E-Print Network [OSTI]

Student Regulations and Procedures Academic Division 2007/2008 3 RULES FOR STUDENT CONDUCT fees, award ceremonies and other matters www.mmu.ac.uk/academic/student_regulations.php #12;RULES of Governors in accordance with the following Articles of Government: 7.1.6 Subject to the responsibilities

480

DIVISION S-6--SOIL & WATER MANAGEMENT & CONSERVATION  

E-Print Network [OSTI]

DIVISION S-6--SOIL & WATER MANAGEMENT & CONSERVATION Soil Organic Carbon Sequestration Rates soil column within 20 yr following culti- Carbon sequestration rates, with a change from CT to NT, can in approximately 40 to and returning to the original land cover or other peren- 60 yr. Carbon sequestration rates

Note: This page contains sample records for the topic "forecasting division mark" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

ENVIRONMENT, SAFETY & HEALTH DIVISION Chapter 24: Training  

E-Print Network [OSTI]

ENVIRONMENT, SAFETY & HEALTH DIVISION Chapter 24: Training Quick Start Summary Product ID: 520-group.slac.stanford.edu/esh/eshmanual/references/trainingQuickstart.pdf 1 Who needs to know about these requirements The requirements of Training apply to all persons on-site, employees and non-employees, their SLAC

Wechsler, Risa H.

482

Division of Human Resources University Grievance Procedures  

E-Print Network [OSTI]

Division of Human Resources University Grievance Procedures Employee Relations/ USF System Grievance Procedure Questions: (813) 974-2970 Rev. 12/2012 This procedure applies to Administration, Staff in this procedure are expressed in calendar days. If a deadline falls on a Saturday, Sunday or holiday, an action

Meyers, Steven D.

483

UNIVERSITY OF SASKATCHEWAN FACILITIES MANAGEMENT DIVISION  

E-Print Network [OSTI]

UNIVERSITY OF SASKATCHEWAN FACILITIES MANAGEMENT DIVISION POLICY Policy Number: 310.1 Approvals at the University of Saskatchewan. In addition, it will provide other administrative and academic units at the University of Saskatchewan with a model for sustainability in their respective workplaces. Policy Statement

Peak, Derek

484

Materials Sciences Division 1990 annual report  

SciTech Connect (OSTI)

This report is the Materials Sciences Division's annual report. It contains abstracts describing materials research at the National Center for Electron Microscopy, and for research groups in metallurgy, solid-state physics, materials chemistry, electrochemical energy storage, electronic materials, surface science and catalysis, ceramic science, high tc superconductivity, polymers, composites, and high performance metals.

Not Available

1990-01-01T23:59:59.000Z

485

West Virginia University Division of Human Resources  

E-Print Network [OSTI]

Resources Web page hr.wvu.edu. In the event of a conflict between the current posted version and this printed copy, the posted version on the Web page is controlling. Page 1 of 9 Family Medical Leave Act Division of Human Resources Web page hr.wvu.edu. In the event of a conflict between the current posted

Mohaghegh, Shahab

486

Earth Science Division Overview Unidata Policy Committee  

E-Print Network [OSTI]

Science Division Focus Areas Shanghai Beijing #12;USGCRP NACP: North American Carbon Program http on Earth's climate, the ozone layer and how much solar energy the Earth retains. To improve our and Ecosystems Climate Variability and Change Weather Water and Energy Cycle Earth Surface and Interior Earth

487

Building an R package Division of Biostatistics  

E-Print Network [OSTI]

Building an R package Yen-Yi Ho Division of Biostatistics School of Public Health, University of Minnesota Yen-Yi Ho Building an R package #12;Steps Prepare your functions, example data sets Build package in man subdirectory) Write a package vignette Build and install the R package (R CMD build) Check the R

Carlin, Bradley P.

488

SHORT-TUBE SUBCRITICAL FLOW Enerag Division  

E-Print Network [OSTI]

#12;SHORT-TUBE SUBCRITICAL FLOW Y. C. Mei Enerag Division Oak Ridge National Laboratory Oak Ridge-tube subcritical flow. For short tubes used as refrigerant expansion devices, the orifice model is found inadequate-TUBE SUBCRITICAL FLOW INTRODUCTION Much theoretical and experimental work regarding short tube fluid flow has

Oak Ridge National Laboratory

489

Division of Human Resources Payroll Certification Process  

E-Print Network [OSTI]

Division of Human Resources Payroll Certification Process Questions (813) 974-7955 Payroll/Payroll Processing Rev. 04/2010 Payroll Certification is the process by which departments submit to Payroll the hours to be paid for each employee within each department. This process utilizes the online Certification System

Meyers, Steven D.

490

Energy Technology Division research summary 1997.  

SciTech Connect (OSTI)

The Energy Technology Division provides materials and engineering technology support to a wide range of programs important to the US Department of Energy. As shown on the preceding page, the Division is organized into ten sections, five with concentrations in the materials area and five in engineering technology. Materials expertise includes fabrication, mechanical properties, corrosion, friction and lubrication, and irradiation effects. Our major engineering strengths are in heat and mass flow, sensors and instrumentation, nondestructive testing, transportation, and electromechanics and superconductivity applications. The Division Safety Coordinator, Environmental Compliance Officers, Quality Assurance Representative, Financial Administrator, and Communication Coordinator report directly to the Division Director. The Division Director is personally responsible for cultural diversity and is a member of the Laboratory-wide Cultural Diversity Advisory Committee. The Division's capabilities are generally applied to issues associated with energy production, transportation, utilization or conservation, or with environmental issues linked to energy. As shown in the organization chart on the next page, the Division reports administratively to the Associate Laboratory Director (ALD) for Energy and Environmental Science and Technology (EEST) through the General Manager for Environmental and Industrial Technologies. While most of our programs are under the purview of the EEST ALD, we also have had programs funded under every one of the ALDs. Some of our research in superconductivity is funded through the Physical Research Program ALD. We also continue to work on a number of nuclear-energy-related programs under the ALD for Engineering Research. Detailed descriptions of our programs on a section-by-section basis are provided in the remainder of this book. This Overview highlights some major trends. Research related to the operational safety of commercial light water nuclear reactors (LWRS) is funded by the US Nuclear Regulatory Commission (NRC). In addition to our ongoing work on environmentally assisted cracking and steam generator integrity, a major new multiyear program has been initiated to assess the performance of high-burnup fuel during loss-of-coolant accidents. The bulk of the NRC research work is carried out in four ET sections: Corrosion: Mechanics of Materials; Irradiation Performance: and Sensors, Instrumentation, and Nondestructive Evaluation. The Transportation of Hazardous Materials Section is the other main contributor; staff from that Section have worked closely with NRC staff to draft a new version of the NRC Standard Review Plan that will be used to provide guidance to NRC reviewers of applications for the renewal of nuclear plant licenses.

NONE

1997-10-21T23:59:59.000Z

491

Department of Natural Resources and Water Divisions (Nebraska)  

Broader source: Energy.gov [DOE]

This chapter describes the duties of the Department of Natural Resources and divides the state into two water divisions for administrative purposes. Water Division 1 consists of all the lands of...

492

Nuclear Science Division Annual Report 1995-1996  

E-Print Network [OSTI]

Saladin5, and C.H. Yu6 Nuclear Science Division, LawrenceMoretto, G.J. Wozniak, Nuclear Science Division, LawrenceComment on Probing the Nuclear Liquid-Gas Phase Transition

Authors, Various

2010-01-01T23:59:59.000Z

493

Linking Sulfur Metabolism to the Cell Division Machinery in Yeast  

E-Print Network [OSTI]

The longstanding view has been that metabolism allows for cell division to take place, but that metabolic processes do not actively promote cell division. I have recently challenged this notion by identifying a unique gain-of-function metabolic...

Blank, Heidi M.

2010-07-14T23:59:59.000Z

494

The mechanism of chloroplast division in higher plants  

E-Print Network [OSTI]

of chloroplasts found in a normal mesophyll cell. The process of chloroplast biogenesis has been well characterized at the cellular level, but the molecular basis of chloroplast division and the role of nuclear genes in the control of plastid division...

Proctor, John Michael

2013-02-22T23:59:59.000Z

495

Heavy Metals in Glass Beads Used in Pavement Markings  

E-Print Network [OSTI]

Pavement markings are vital for safely navigating roadways. The nighttime visibility of pavement markings is enhanced by addition of retroreflective glass beads, most of which are made from recycled glass. Concern has been raised over the presence...

Mangalgiri, Kiranmayi

2012-07-16T23:59:59.000Z

496

Synergies in learning words and their referents Mark Johnson  

E-Print Network [OSTI]

Synergies in learning words and their referents Mark Johnson Department of Computing Macquarie University Sydney, NSW 2109 Mark.Johnson@mq.edu.au Katherine Demuth Department of Linguistics Macquarie

Edinburgh, University of

497

ANL Physics DivisionANL Physics Division ELECTRICAL SAFETY POLICY AND MANUAL  

E-Print Network [OSTI]

ON ENERGIZED CIRCUITS XV. LOCKOUT/TAGOUT XVI. TABLES The official version of this Physics Division manual annually. Ensures or oversees completion of the annual review of Lockout/Tagout procedures and authorized

Kemner, Ken

498

INTRAMURAL GOLF TOURAMENT ALL DIVISIONS Fall 2011 Division Sunday Sept. 18  

E-Print Network [OSTI]

INTRAMURAL GOLF TOURAMENT ALL DIVISIONS Fall 2011 Division Sunday Sept. 18 GOLF M W Team Member ?? EMAIL Tee-Time FIRST NAME LAST NAME or F TEAM NAME @psu.edu 9:00 AM Matt McTague M last round mim5187 Frankie Kehs M last round fjk5012 Chase Roman M Tiger Wood cer197 Dustin Hartzel M Tiger Wood dnh124 9

Omiecinski, Curtis

499

Forecasting Volatility in Stock Market Using GARCH Models  

E-Print Network [OSTI]

Forecasting volatility has held the attention of academics and practitioners all over the world. The objective for this master's thesis is to predict the volatility in stock market by using generalized autoregressive conditional heteroscedasticity(GARCH...

Yang, Xiaorong

2008-01-01T23:59:59.000Z

500

Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap  

E-Print Network [OSTI]

Forecasting Returns and Volatilities in GARCH Processes Using the Bootstrap Lorenzo Pascual, Juan generated by GARCH processes. The main advantage over other bootstrap methods previously proposed for GARCH by having conditional heteroscedasticity. Generalized Autoregressive Conditionally Heteroscedastic (GARCH

Romo, Juan