DocumentCode :
3036695
Title :
Genetic evolution of regression models for business and economic forecasting
Author :
Kaboudan, M.A.
Author_Institution :
Penn State, Smeal Coll. of Bus. Adm., Fogelsville, PA, USA
Volume :
2
fYear :
1999
fDate :
1999
Abstract :
The paper attempts to bridge the gap between genetic evolution of regression models and their use in business and economic forecasting. With ample evidence of their successful fitting of data from fairly complex systems, a logical next step is to make genetic and evolutionary methods useful and available to business and economics researchers. A few suggestions are made; they describe desirable output files and statistical tests to evaluate results from evolved models which genetic or evolutionary computer programs should produce. These suggestions should invite better ones to popularize use of evolutionary methodology and to benefit scientific research
Keywords :
business data processing; economics; forecasting theory; genetic algorithms; statistical analysis; business; complex systems; data fitting; economic forecasting; economics researchers; evolutionary computer programs; evolutionary methodology; evolutionary methods; genetic evolution; output files; regression models; scientific research; statistical tests; Bridges; Economic forecasting; Educational institutions; Genetic programming; Information management; Management information systems; Prediction methods; Predictive models; Testing; Usability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5536-9
Type :
conf
DOI :
10.1109/CEC.1999.782587
Filename :
782587
Link To Document :
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