计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (18): 44-47.

• 理论研究 • 上一篇    下一篇

基于BP神经网络的模糊参数辨识

韦卫星,磨少清,覃春芳,廖义奎,文 勇   

  1. 广西民族大学 物理与电子工程学院,南宁 530006
  • 收稿日期:2007-09-19 修回日期:2007-12-13 出版日期:2008-06-21 发布日期:2008-06-21
  • 通讯作者: 韦卫星

Fuzzy parameters identification based on BP neural network

WEI Wei-xing,MO Shao-qing,QIN Chun-fang,LIAO Yi-kui,WEN Yong   

  1. College of Physics and Electronic Engineering,Guangxi University for Nationalities,Nanning 530006,China
  • Received:2007-09-19 Revised:2007-12-13 Online:2008-06-21 Published:2008-06-21
  • Contact: WEI Wei-xing

摘要: 提出一种与TSK模糊模型相似的模糊模型—M-2模型,证明了M-2模型与一个4层前向神经网络是等价的,在此基础上提出基于BP神经网络的模糊模型参数辨别算法,即通过BP神经网络对样本数据的学习,直接从样本数据获取模型参数,建立M-2模糊模型,通过仿真实例验证了该算法的有效性。

Abstract: A fuzzy model called M-2 model which is similar to TSK fuzzy model is proposed.The mathematical equivalence between M-2 model and a 4 layer feedforward neural network is verified.Then a new algorithm to identify parameters of fuzzy model based on BP neural network is put forward.All parameters required for establishing M-2 fuzzy model are extracted directly from a BP neural network trained by sample data.A simulation example is given to demonstrate the effectiveness of the algorithm.