Design for Self-Organizing Fuzzy Neural Networks Based on Adaptive Evolutionary Programming

摘要：

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 higb 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.

关键词： Fuzzy Neural Networks evolutionary programming fuzzy rule

作者: LIU Fang

作者单位: School of Electroruc Information & Control Engineering, Beijing University of Technology Beijing,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 251-254

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）