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A fuzzy neural network evolved by particle swarm optimization
作者姓名:彭志平  彭宏
作者单位:[1]Dept. of Computer Science & Technology, Maoming College, Maoming 525000, China [2]School of Computer Science & Engineering, South China University of Teehnology. Guangzhou 510640, China
摘    要:A cooperative system of a fuzzy logic model and a fuzzy neural network(CSFLMFNN)is proposed,in which a fuzzy logic model is acquired from domain experts and a fuzzy neural network is generated and prewired according to the model.Then PSO-CSFLMFNN is constructed by introducing particle swarm optimization(PSO)into the cooperative system instead of the commonly used evolutionary algorithms to evolve the prewired fuzzy neural network.The evolutionary fuzzy neural network implements accuracy fuzzy inference without rule matching.PSO-CSFLMFNN is applied to the intelligent fault diagnosis for a petrochemical engineering equipment,in which the cooperative system is proved to be effective.It is shown by the applied results that the performance of the evolutionary fuzzy neural network outperforms remarkably that of the one evolved by genetic algorithm in the convergence rate and the generalization precision.

关 键 词:模糊神经网络  颗粒群最优化  智能故障诊断  模糊逻辑系统
文章编号:1005-9113(2007)03-0316-06
修稿时间:2006-06-08

A fuzzy neural network evolved by particle swarm optimization
PENG Zhi-ping,PENG Hong.A fuzzy neural network evolved by particle swarm optimization[J].Journal of Harbin Institute of Technology,2007,14(3):316-321.
Authors:PENG Zhi-ping  PENG Hong
Abstract:A cooperative system of a fuzzy logic model and a fuzzy neural network(CSFLMFNN)is proposed,in which a fuzzy logic model is acquired from domain experts and a fuzzy neural network is generated and prewired according to the model.Then PSO-CSFLMFNN is constructed by introducing particle swarm optimization(PSO)into the cooperative system instead of the commonly used evolutionary algorithms to evolve the prewired fuzzy neural network.The evolutionary fuzzy neural network implements accuracy fuzzy inference without rule matching.PSO-CSFLMFNN is applied to the intelligent fault diagnosis for a petrochemical engineering equipment,in which the cooperative system is proved to be effective.It is shown by the applied results that the performance of the evolutionary fuzzy neural network outperforms remarkably that of the one evolved by genetic algorithm in the convergence rate and the generalization precision.
Keywords:fuzzy neural network  evolving  particle swarm optimization  intelligent fault diagnosis
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