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
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;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870794