An Effective Initialization for Fuzzy Wavelet Neural Networks In Nonlinear System Identification

摘要：

This paper presents a Fuzzy Wavelet Neural Network (FWNN) for nonlinear dynamic system identification and includes an effective clustering algorithm for determining the initial structure and parameters of the FWNN.The FWNN is constructed on the basis of fuzzy rules that incorporate wavelet functions in their consequent parts.The main purpose is applying a good initialization procedure in FWNN so that fast convergence and satisfactory result can be obtained.A simple and effective clustering method is presented for the FWNN to reduce the number of fuzzy rules and speed up the convergence.The proposed approach is tested for identification of nonlinear dynamic plants commonly used in the literature.It is shown that with the proposed approach the number of rules and complexity of the structure will be reduced while the performance is better than the previous works.

关键词： Fuzzy wavelet neural networks Initialization Data Clustering System identification

作者: Mehrnoosh Davanipoor Farid Sheikholeslam Maryam Zekri

作者单位: Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan,Iran

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 48-51

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）