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作者:

Liu Fang (Liu Fang.)

收录:

CPCI-S EI Scopus

摘要:

A novel hybrid learning algorithm based on a evolutionary programming to design a growing fuzzy neural network, named self-organizing fuzzy neural network based on evolutionary programming, to implement Takagi-Sugeno(TS) type fuzzy models is proposed in this paper. construct and parameters of the fuzzy neural network is trained by evolutionary algorithms. Simulation results demonstrate that a compact and high performance fuzzy rule base can be constructed. Comprehensive comparisons with other approach show that the proposed approach is superior over other in terms of learning efficiency and performance.

关键词:

evolutionary programming Fuzzy Neural Networks fuzzy rule

作者机构:

  • [ 1 ] Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China

通讯作者信息:

  • [Liu Fang]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China

电子邮件地址:

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来源 :

2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 3

年份: 2010

页码: 251-254

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

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