DocumentCode :
296219
Title :
Application of genetic algorithms in fuzzy rules generation
Author :
Makrehchi, Masoud
Volume :
1
fYear :
1995
fDate :
Nov. 29 1995-Dec. 1 1995
Firstpage :
251
Abstract :
In this paper, identification of fuzzy rules is discussed, and a new method for modeling of fuzzy rules is proposed. In the proposed method, set of fuzzy parameters are assigned to the consequents of each fuzzy rule and a genetic algorithm is provided for optimization of these parameters. The procedure is implemented on a multivariable dynamic model and results of extensive simulation studies are presented to demonstrate the performance of this method in designing multivariable fuzzy controllers
Keywords :
Control systems; Differential equations; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematical model; Optimization methods; Search problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA, Australia
Print_ISBN :
0-7803-2759-4
Type :
conf
DOI :
10.1109/ICEC.1995.489154
Filename :
489154
Link To Document :
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