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Author:

Liu Fang (Liu Fang.)

Indexed by:

CPCI-S EI Scopus

Abstract:

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.

Keyword:

Fuzzy Neural Networks fuzzy rule evolutionary programming

Author Community:

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

Reprint Author's Address:

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

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Source :

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

Year: 2010

Page: 251-254

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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