DocumentCode
2444668
Title
A framework of fuzzy modeling using genetic algorithms with appropriate combination of evaluation criteria
Author
Suzuki, Toshihiro ; Furuhashi, Takeshi ; Tsutsui, Hiroaki
Author_Institution
Dept. of Inf. Electron., Nagoya Univ., Japan
Volume
2
fYear
2000
fDate
2000
Firstpage
1252
Abstract
Fuzzy modeling is a method to describe nonlinear input-output relationships. Genetic algorithms (GAs) have been used with fuzzy modeling for identification of the structure of a fuzzy model and selection of input variables. Users often require fuzzy models that satisfy multiple evaluation criteria. Assignment of appropriate weights on these criteria is one of the key factors for good GA search. In order to give a guideline for assigning the degree of importance to each evaluation criterion for generating fuzzy models, we examined the characteristic of each evaluation criterion
Keywords
fuzzy logic; genetic algorithms; identification; modelling; evaluation criteria; fuzzy modeling; genetic algorithms; input variables; nonlinear input-output relationships; search; Character generation; Chromium; Cybernetics; Genetic algorithms; Guidelines; Humans; Input variables; Performance evaluation; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location
La Jolla, CA
Print_ISBN
0-7803-6375-2
Type
conf
DOI
10.1109/CEC.2000.870794
Filename
870794
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