Fuzzy neural classifier for transformer fault diagnosis based on EM learning

被引：0
|
作者：
Su, Hongsheng [1 ]
Li, Qunzhan [1 ]
机构：
[1] SW Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Peoples R China
来源：
COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS | 2006年 / 4114卷
关键词：
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：
A novel fuzzy neural classifier and learning algorithm are proposed based on EM learning in this paper. The method firstly applies rough set of its information measurement ability to evaluate system parameters importance. Then, based on EM learning the unknown parameters of fuzzy member functions are estimated. Then a fuzzy neural classifier based on EM algorithm is generated. The research indicates that the proposed network possesses higher diagnosis precision and speed as well as excellent anti-interference abilities, and is an ideal pattern classifier. In the end, a practical application in transformer fault diagnosis shows the availability of the method.
引用
收藏
页码：222 / 229
页数：8
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