Recursive Particle Swarm Optimization Applications In Radial Basis Function Networks Modeling System

摘要：

A novel strategy on particle swarm optimization is proposed to solve dynamic optimization problems, in which the data are obtained not once for all but one by one. The evolutionary states of the particle swarm are guided recursively by the proposed algorithm, according to the information achieved by the continuous data and the prior estimated knowledge on the solution space. The experimental results for three test functions show that radial basis function networks modeling system based on the proposed recursive algorithm requires fewer radial basis functions and gives more accurate results than other traditional improved PSO in solving dynamic problems.

关键词： PSO Recursive Radial Basis Function Networks Modeling System

作者: Baolei Li Xinlin Shi Jianhua Chen Zhenzhou An Huawei Ding Xiaofeng Wang

作者单位: School of Information Science and Engineering Yunnan University Kunming, China

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 1789-1792

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）