DocumentCode
1563041
Title
Using genetic algorithm for weighted fuzzy rule-based system
Author
Teng, Minggui ; Xiong, FanLun ; Wang, Rujing ; Wu, Zhenglong
Author_Institution
Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei, China
Volume
5
fYear
2004
Firstpage
4292
Abstract
A genetic weighted fuzzy rule-based system is proposed in this paper, in which the parameters of membership functions including position and shape of the fuzzy rule set and weights of rules are evolved using a genetic algorithm. The efficiency of the system has been illustrated in the process of classifying the iris data. This paper also illustrates that compared with non-weighted fuzzy rules, weighted fuzzy rules can lead to better fuzzy system.
Keywords
fuzzy set theory; fuzzy systems; genetic algorithms; knowledge based systems; fuzzy rule set theory; fuzzy system; genetic algorithm; membership functions; nonweighted fuzzy rules; weighted fuzzy rule based system; Biological cells; Content addressable storage; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Iris; Knowledge based systems; Machine intelligence; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN
0-7803-8273-0
Type
conf
DOI
10.1109/WCICA.2004.1342321
Filename
1342321
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