Optimization Algorithm Based on T-S Fuzzy Model of Self-adaptive Disturbed Particle Swarm Optimization and Neural Network

摘要：

To solve fuzzy and non-linear features of mechanical equipment. A new computational intelligence method was proposed by combing based on extended T-S fuzzy model of self-adaptive disturbed PSO and BP neural network algorithm. Firstly, the T-S fuzzy model is modified, and then uses the extended T-S model to adjust the PSO parameter. Secondly, the neural network is trained by the modified PSO algorithm. Finally, a wheel disc model is optimized to check that network model, the test results show that it guarantees the performance of the wheel disc, meanwhile the wheel disc structure is obviously optimized, and the algorithm in the paper is a method of viable structure optimization.

关键词： Fuzzy model Particle Swarm Optimization BP Neural network Optimization

作者: Wang Jianfang Li Weihua

作者单位: College of Computer Northwestern Polytechnical University Xi’an, P. R. China

会议类型: 国际会议

会议名称: 2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)

会议地点: 沈阳

会议语种:英文

页码: 1-5

在线出版日期: 2009-08-12（万方平台首次上网日期，不代表论文的发表时间）