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Nonlinear systems modeling using LS-SVM with SMO-based pruning methods

  • Hohai University
  • Southeast University, Nanjing

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper firstly provides a short introduction to least square support vector machine (LS-SVM), then provides sequential minimal optimization (SMO) based on Pruning Algorithms for LS-SVM, and uses LSSVM to model nonlinear systems. Simulation experiments are performed and indicated that the proposed method provides satisfactory performance with excellent accuracy and generalization property and achieves superior performance to the conventional method based on common LS-SVM and neural networks.

源语言英语
主期刊名Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
出版商Springer Verlag
618-625
页数8
版本PART 1
ISBN(印刷版)9783540723820
DOI
出版状态已出版 - 2007
已对外发布
活动4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, 中国
期限: 3 6月 20077 6月 2007

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
编号PART 1
4491 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议4th International Symposium on Neural Networks, ISNN 2007
国家/地区中国
Nanjing
时期3/06/077/06/07

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