This method has been used successfully for work in short-term forecasting. It may be used for any weather variable, such as temperature, precipitation, wave height, wind velocity, or severe storms.
Preparations for a disruptive event is often expensive and companies are better positioned to take appropriate action when the probability of such an event is known. The computation time for the forecasts is very short; decisions can be made in real-time.
This Evolved Program Analytical Forecasts method is an automated process that uses any large data set as an input, and algorithms evolve by a method called Simulated Evolution giving the probabilities of different outcomes based on the information desired. This new method also accounts for the spatial dimension of the data. The approach is based upon predator-prey ecosystem dynamics, in which the predators fill the role of regulators of the population that carries the forecast information. A forecast solution carrier is produced by using steady population, which drives progress towards improved forecast solutions. An automated process which needs the supervision of only one trained forecaster brings down costs and makes short-term forecasts accessible to a greater number of businesses and organizations.
This is a copyrighted work available for developmental research support and licensing under either exclusive or non-exclusive terms. We are interested in companies who would like to team up to create a website that can be used globally. We are also interested in licensing the algorithms to companies as well as seeking specific companies and industries in need of specialized forecasting. The technology is.
Dr. Paul Roebber, PhD – Distinguished Professor in the Department of Mathematical Sciences at the University of Wisconsin-Milwaukee.
For further information please contact:
Jessica Silvaggi, Ph.D.
Director of Technology Commercialization
UWM Research Foundation
1440 East North Avenue
Milwaukee, WI 53202
Please reference: OTT ID. 1239