Force identification by using support vector machine and differential evolution optimization

Zhichao Fu; Wei Cheng

doi:10.1007/978-3-642-12990-2_92

Force identification by using support vector machine and differential evolution optimization

Zhichao Fu^*
, Wei Cheng

^*Corresponding author for this work

School of Mechanical Engineering and Automation

Beihang University

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

1 Scopus citations

Abstract

A novel method is presented to determine the external dynamic forces applied on structures from measured structural responses in this paper. The method utilizes a new SVM-DE model that hybridized the differential evolution (DE) technique and support vector machines (SVM) to resolve the problem of force identification. Both numerical simulations and experimental study are conducted to demonstrate the effectiveness, robustness and applicability of the proposed method. It is promising that the proposed method is practical to the real-life application.

Original language	English
Title of host publication	Advances in Neural Network Research and Applications
Pages	793-801
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-642-12990-2_92
State	Published - 2010
Event	7th International Symposium on Neural Networks, ISNN 2010 - Shanghai, China Duration: 6 Jun 2010 → 9 Jun 2010

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	67 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	7th International Symposium on Neural Networks, ISNN 2010
Country/Territory	China
City	Shanghai
Period	6/06/10 → 9/06/10

Keywords

Differential evolution
Force identification
Support vector machine

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10.1007/978-3-642-12990-2_92

Cite this

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title = "Force identification by using support vector machine and differential evolution optimization",

abstract = "A novel method is presented to determine the external dynamic forces applied on structures from measured structural responses in this paper. The method utilizes a new SVM-DE model that hybridized the differential evolution (DE) technique and support vector machines (SVM) to resolve the problem of force identification. Both numerical simulations and experimental study are conducted to demonstrate the effectiveness, robustness and applicability of the proposed method. It is promising that the proposed method is practical to the real-life application.",

keywords = "Differential evolution, Force identification, Support vector machine",

author = "Zhichao Fu and Wei Cheng",

year = "2010",

doi = "10.1007/978-3-642-12990-2\_92",

language = "英语",

isbn = "9783642129896",

series = "Lecture Notes in Electrical Engineering",

pages = "793--801",

booktitle = "Advances in Neural Network Research and Applications",

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}

Fu, Z & Cheng, W 2010, Force identification by using support vector machine and differential evolution optimization. in Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol. 67 LNEE, pp. 793-801, 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, 6/06/10. https://doi.org/10.1007/978-3-642-12990-2_92

TY - GEN

T1 - Force identification by using support vector machine and differential evolution optimization

AU - Fu, Zhichao

AU - Cheng, Wei

PY - 2010

Y1 - 2010

N2 - A novel method is presented to determine the external dynamic forces applied on structures from measured structural responses in this paper. The method utilizes a new SVM-DE model that hybridized the differential evolution (DE) technique and support vector machines (SVM) to resolve the problem of force identification. Both numerical simulations and experimental study are conducted to demonstrate the effectiveness, robustness and applicability of the proposed method. It is promising that the proposed method is practical to the real-life application.

AB - A novel method is presented to determine the external dynamic forces applied on structures from measured structural responses in this paper. The method utilizes a new SVM-DE model that hybridized the differential evolution (DE) technique and support vector machines (SVM) to resolve the problem of force identification. Both numerical simulations and experimental study are conducted to demonstrate the effectiveness, robustness and applicability of the proposed method. It is promising that the proposed method is practical to the real-life application.

KW - Differential evolution

KW - Force identification

KW - Support vector machine

UR - https://www.scopus.com/pages/publications/84867352232

U2 - 10.1007/978-3-642-12990-2_92

DO - 10.1007/978-3-642-12990-2_92

M3 - 会议稿件

AN - SCOPUS:84867352232

SN - 9783642129896

T3 - Lecture Notes in Electrical Engineering

SP - 793

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BT - Advances in Neural Network Research and Applications

T2 - 7th International Symposium on Neural Networks, ISNN 2010

Y2 - 6 June 2010 through 9 June 2010

ER -

Force identification by using support vector machine and differential evolution optimization

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Keywords

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