A new genetic algorithm for nonlinear multiregressions based on generalized Choquet integrals

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 22 Mar 2004Publisher:IEEEJournal:The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03., volume 2, pages 819-821

Authors: Zhenyuan Wang; Hai-Feng Guo;

doi: 10.1109/fuzz.2003.1206535

A new genetic algorithm for nonlinear multiregressions based on generalized Choquet integrals

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Abstract

This paper gives a new genetic algorithm for nonlinear multiregression based on generalized Choquet integrals with respect to signed fuzzy measures. Unlike the previous work where the values of the signed fuzzy measure are determined by random search in a genetic algorithm with other regression coefficients together; in this new algorithm, they are determined algebraically and, therefore, its complexity is much lower than before.

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University of Nebraska at Omaha
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