数学季刊 ›› 1999, Vol. 14 ›› Issue (3): 30-35.

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基于BP网络和RBF网络的模糊系统建模

  

  1.  Faculty of Computer Science and Technology,Henan University,Kaifeng,475001; Department of Applied Mathematics,Southwest Jiaotong University,Chengdu,610031;Commerce University of Chongqing

  • 收稿日期:1999-01-05 出版日期:1999-09-30 发布日期:2024-09-11
  • 基金资助:
    Supported by National Natural Science Foundation of China ( Grant No.69674015,69874033) .

On Modeling a Fuzzy System Based on BPN and RBFN

  1.  Faculty of Computer Science and Technology,Henan University,Kaifeng,475001; Department of Applied Mathematics,Southwest Jiaotong University,Chengdu,610031;Commerce University of Chongqing
  • Received:1999-01-05 Online:1999-09-30 Published:2024-09-11
  • Supported by:
    Supported by National Natural Science Foundation of China ( Grant No.69674015,69874033) .

摘要: This paper presents a method of modeling a fuzzy system with fuzzy and nonlinear border,obtaining systematic structure by clustering analysis,applying BP network ( BPN) to generate rule baseˋs antecedent function and using RBF network ( RBFN) to approximate each ruleˋs conclusion function not only because of efficient capability of approximation nonlinear function of BPN and RBFN but also because of quickness of training speed of RBFN.In addition,structure design and training of relevant networks are discussed in detail.Finally,the structure optimization and overstudy of RBFN are discussed.

关键词: BP network, RBF network, clustering analysis, modeling

Abstract: This paper presents a method of modeling a fuzzy system with fuzzy and nonlinear border,obtaining systematic structure by clustering analysis,applying BP network ( BPN) to generate rule baseˋs antecedent function and using RBF network ( RBFN) to approximate each ruleˋs conclusion function not only because of efficient capability of approximation nonlinear function of BPN and RBFN but also because of quickness of training speed of RBFN.In addition,structure design and training of relevant networks are discussed in detail.Finally,the structure optimization and overstudy of RBFN are discussed.

Key words: BP network, RBF network, clustering analysis, modeling

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