Using genetic algorithm for weighted fuzzy rule-based system

Minggui Teng, Fanlun Xiong, Rujing Wang, Zhenglong Wu · 2004

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.

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