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A RBF neural network learning algorithm based on NCPSO

  • Southeast University, Nanjing

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

A RBF (Radial Basis Function) neural network learning algorithm based on NCPSO (Niching Chaotic Mutation Particle Swarm Optimization) is proposed. Because of the niching method and chaotic mutation, NCPSO can be used to optimize the output weights of the RBF Neural Network. Niching method is introduced to improve the ability of global optimization. Chaotic mutation is mentioned to improve the solution. Compared with the RBF neural network learning algorithm based on the GA (Genetic Algorithm), simulation shows that the RBF neural network learning algorithm based on NCPSO mentioned in this paper has a lower error of tracking and higher speed.

源语言英语
主期刊名Proceedings of the 32nd Chinese Control Conference, CCC 2013
出版商IEEE Computer Society
3294-3299
页数6
ISBN(印刷版)9789881563835
出版状态已出版 - 18 10月 2013
已对外发布
活动32nd Chinese Control Conference, CCC 2013 - Xi'an, 中国
期限: 26 7月 201328 7月 2013

出版系列

姓名Chinese Control Conference, CCC
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议32nd Chinese Control Conference, CCC 2013
国家/地区中国
Xi'an
时期26/07/1328/07/13

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