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Title: System and method of designing models in a feedback loop

Abstract

A method and system for designing models is disclosed. The method includes selecting a plurality of models for modeling a common event of interest. The method further includes aggregating the results of the models and analyzing each model compared to the aggregate result to obtain comparative information. The method also includes providing the information back to the plurality of models to design more accurate models through a feedback loop.

Inventors:
; ;
Issue Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1343748
Patent Number(s):
9569732
Application Number:
13/869,290
Assignee:
BATTELLE MEMORIAL INSTITUTE
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Apr 24
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; 42 ENGINEERING

Citation Formats

Gosink, Luke C., Pulsipher, Trenton C., and Sego, Landon H. System and method of designing models in a feedback loop. United States: N. p., 2017. Web.
Gosink, Luke C., Pulsipher, Trenton C., & Sego, Landon H. System and method of designing models in a feedback loop. United States.
Gosink, Luke C., Pulsipher, Trenton C., and Sego, Landon H. Tue . "System and method of designing models in a feedback loop". United States. https://www.osti.gov/servlets/purl/1343748.
@article{osti_1343748,
title = {System and method of designing models in a feedback loop},
author = {Gosink, Luke C. and Pulsipher, Trenton C. and Sego, Landon H.},
abstractNote = {A method and system for designing models is disclosed. The method includes selecting a plurality of models for modeling a common event of interest. The method further includes aggregating the results of the models and analyzing each model compared to the aggregate result to obtain comparative information. The method also includes providing the information back to the plurality of models to design more accurate models through a feedback loop.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {2}
}

Works referenced in this record:

Using Bayesian Model Averaging to Calibrate Forecast Ensembles
journal, May 2005


Multi-objective calibration of forecast ensembles using Bayesian model averaging
journal, January 2006


Bagging predictors
journal, August 1996


Model uncertainty and model inaccuracy
journal, February 1998


Maximum likelihood Bayesian averaging of airflow models in unsaturated fractured tuff using Occam and variance windows
journal, March 2010


Ensemble-based classifiers
journal, November 2009