Fuzzy rule generation with fuzzy singleton-type reasoning method

被引：0
|
作者：
Shi, Y
Mizumoto, M
机构：
来源：
NEW PARADIGM OF KNOWLEDGE ENGINEERING BY SOFT COMPUTING | 2001年 / 5卷
关键词：
fuzzy singleton-type reasoning method; fuzzy rule generation; neuro-fuzzy learning algorithm; fuzzy c-means clustering algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
By means of fuzzy singleton-type reasoning method, we propose a self-tuning method for fuzzy rule generation. In this tuning approach, first we use a learning algorithm for tuning fuzzy rules under fuzzy singleton-type reasoning method, then we roughly design initial tuning parameters of fuzzy rules based on fuzzy clustering algorithm. By this approach, the learning time can be reduced and the fuzzy rules generated are reasonable and suitable for identified system model. Finally, we show the efficiency of the employed method by identifying nonlinear functions.
引用
收藏
页码：59 / 76
页数：18
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