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

Changyin Sun; Jinya Song; Guofang Lv; Hua Liang

doi:10.1007/978-3-540-72383-7_73

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

Changyin Sun
, Jinya Song
, Guofang Lv
, Hua Liang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Publisher	Springer Verlag
Pages	618-625
Number of pages	8
Edition	PART 1
ISBN (Print)	9783540723820
DOIs	https://doi.org/10.1007/978-3-540-72383-7_73
State	Published - 2007
Externally published	Yes
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 3 Jun 2007 → 7 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4491 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	3/06/07 → 7/06/07

Access to Document

10.1007/978-3-540-72383-7_73

Cite this

Sun, C., Song, J., Lv, G., & Liang, H. (2007). Nonlinear systems modeling using LS-SVM with SMO-based pruning methods. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 1 ed., pp. 618-625). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_73

Sun, Changyin ; Song, Jinya ; Lv, Guofang et al. / Nonlinear systems modeling using LS-SVM with SMO-based pruning methods. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 618-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{a9ea16a9abac409c89837362f84576c3,

title = "Nonlinear systems modeling using LS-SVM with SMO-based pruning methods",

abstract = "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.",

author = "Changyin Sun and Jinya Song and Guofang Lv and Hua Liang",

year = "2007",

doi = "10.1007/978-3-540-72383-7\_73",

language = "英语",

isbn = "9783540723820",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 1",

pages = "618--625",

booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",

edition = "PART 1",

note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",

}

Sun, C, Song, J, Lv, G & Liang, H 2007, Nonlinear systems modeling using LS-SVM with SMO-based pruning methods. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4491 LNCS, Springer Verlag, pp. 618-625, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 3/06/07. https://doi.org/10.1007/978-3-540-72383-7_73

Nonlinear systems modeling using LS-SVM with SMO-based pruning methods. / Sun, Changyin; Song, Jinya; Lv, Guofang et al.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 618-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sun, Changyin

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PY - 2007

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N2 - 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.

AB - 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.

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DO - 10.1007/978-3-540-72383-7_73

M3 - 会议稿件

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SN - 9783540723820

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings

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T2 - 4th International Symposium on Neural Networks, ISNN 2007

Y2 - 3 June 2007 through 7 June 2007

ER -

Sun C, Song J, Lv G, Liang H. Nonlinear systems modeling using LS-SVM with SMO-based pruning methods. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 618-625. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-72383-7_73

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

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