摘要
本文讨论了基于遗传算法的模糊规则系统,设计了一种加权模糊规则系统,使用遗传算法来学习模糊集隶属函数的位置和形状参数,规则集,包括规则的数目,以及规则的权重.使用Iris数据检验了算法,得到了满意的结果.实验显示,与无权重模糊规则相比,有权重模糊规则能够形成更好的模糊系统。
In this paper, a weighted fuzzy rule-based system has been designed in which the parameters of membership functions including position and type and the fuzzy rule set including the number of rules inside it and weights of rules are tuned using a genetic algorithm. The efficiency of the system has been illustrated in the process of classifying the iris data set. This paper also illustrated that compared with no-weight fuzzy rules, weighted fuzzy rules can lead to better fuzzy system.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2003年第4期506-510,共5页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金(No.69835001)
国家863高科技重点资助项目(No.2001AA115170)
