A Rough-Fuzzy RBF Neural Network Based on PSO Algorithm

摘要：

　　A Rough-Fuzzy RBF Neural Network was raised based on PSO Algorithm.In this model,gives a knowledge acquisition method that based on rough set theory,the Rough-Fuzzy RBF neural network are constructed according to the results of the knowledge acquisition,the PSO are used to optimize the network parameters.This paper take number plate for example to conduct a simulation experiment.The results shows that the model can simplify the network training sample,optimize the network structure and enhance the systems study efficiency and the precision.

关键词： Rough Set Fuzzy RBF neural network PSO algorithm reduction Introduction

作者: Zhao Jing

作者单位: Department of Mechanical and Electrical engineerin Anhui Institute of Architecture & Industry Hefei, China

会议类型: 国际会议

会议名称: 2nd International Conference on Polymer Composities and Polymer Testing (2013第二届高分子复合材料与高分子测试国际会议暨先进工业技术与方案国际会议)(ISPCPT2013)

会议地点: 太原

会议语种:英文

页码: 573-578

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）