DocumentCode
1563814
Title
A new genetic algorithm for nonlinear multiregressions based on generalized Choquet integrals
Author
Wang, Zhenyuan ; Guo, Hai-Feng
Author_Institution
Dept. of Math., Nebraska Univ., Omaha, NE, USA
Volume
2
fYear
2003
Firstpage
819
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.
Keywords
fuzzy set theory; genetic algorithms; integral equations; regression analysis; generalized choquet integrals; genetic algorithm; nonlinear multiregressions; regression coefficients; signed fuzzy measures; Biological cells; Computer science; Data mining; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematics; Power measurement; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN
0-7803-7810-5
Type
conf
DOI
10.1109/FUZZ.2003.1206535
Filename
1206535
Link To Document