Forecasting hotspots using predictive visual analytics approach
Abstract
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.
- Inventors:
- Issue Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1166741
- Patent Number(s):
- 8924332
- Application Number:
- 13/322,626
- Assignee:
- Purdue Research Foundation (West Lafayette, IN)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06F - ELECTRIC DIGITAL DATA PROCESSING
G - PHYSICS G06 - COMPUTING G06Q - DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
- DOE Contract Number:
- AC05-76RL01830
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 2010 May 28
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 58 GEOSCIENCES
Citation Formats
Maciejewski, Ross, Hafen, Ryan, Rudolph, Stephen, Cleveland, William, and Ebert, David. Forecasting hotspots using predictive visual analytics approach. United States: N. p., 2014.
Web.
Maciejewski, Ross, Hafen, Ryan, Rudolph, Stephen, Cleveland, William, & Ebert, David. Forecasting hotspots using predictive visual analytics approach. United States.
Maciejewski, Ross, Hafen, Ryan, Rudolph, Stephen, Cleveland, William, and Ebert, David. Tue .
"Forecasting hotspots using predictive visual analytics approach". United States. https://www.osti.gov/servlets/purl/1166741.
@article{osti_1166741,
title = {Forecasting hotspots using predictive visual analytics approach},
author = {Maciejewski, Ross and Hafen, Ryan and Rudolph, Stephen and Cleveland, William and Ebert, David},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2014},
month = {12}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Understanding syndromic hotspots - a visual analytics approach
conference, October 2008
- Maciejewski, Ross; Rudolph, Stephen; Hafen, Ryan
- 2008 IEEE Symposium on Visual Analytics Science and Technology (VAST)
Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts
journal, April 2009
- Hafen, Ryan P.; Anderson, David E.; Cleveland, William S.
- BMC Medical Informatics and Decision Making, Vol. 9, Issue 1