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
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;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342321
