Takagi-Sugeno Fuzzy Systems Structure Identification Based on Piecewise Linear Initialization

被引:0
作者
Hodashinsky, I. A. [1 ]
Sarin, K. S. [1 ]
Zykov, D. D. [2 ]
机构
[1] Tomsk State Univ Control Syst & Radioelect, Dept Complex Informat Secur, Tomsk, Russia
[2] Tomsk State Univ Control Syst & Radioelect, Natl Res Tomsk Polytech Univ, Tomsk, Russia
来源
2015 INTERNATIONAL SIBERIAN CONFERENCE ON CONTROL AND COMMUNICATIONS (SIBCON) | 2015年
关键词
fuzzy systems; structure identification; machine learning; artificial intelligence;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
A new method is proposed for structure identification of Takagi-Sugeno fuzzy systems, which is called piecewise linear initialization (PLI). This method is based on clustering of input data and has only one parameter: mean-square deviation of a hyperplane in the cluster from data. Each cluster is a particular rule of the fuzzy system. Based on the cluster are constructed Gaussian membership functions, otherwise consequents of fuzzy rules are constructed using the recursive least square method. The proposed method is compared with other methods by analyzing the mean-square error and the average number of rules on various datasets from the KEEL repository.
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页数:4
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