Analog circuit fault diagnosis based on DE-OS-ELM

Shaowei Chen; Minhua Wu; Shuai Zhao

doi:10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM

Shaowei Chen, Minhua Wu, Shuai Zhao

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

4 Citationer (Scopus)

Abstract

Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

Originalsprog	Engelsk
Titel	Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
Antal sider	5
Forlag	IEEE Signal Processing Society
Publikationsdato	19 mar. 2015
Sider	509-513
Artikelnummer	7064245
ISBN (Elektronisk)	9781479970056
DOI	https://doi.org/10.1109/ISCID.2014.94
Status	Udgivet - 19 mar. 2015
Udgivet eksternt	Ja
Begivenhed	7th International Symposium on Computational Intelligence and Design, ISCID 2014 - Hangzhou, Kina Varighed: 13 dec. 2014 → 14 dec. 2014

Konference

Konference	7th International Symposium on Computational Intelligence and Design, ISCID 2014
Land/Område	Kina
By	Hangzhou
Periode	13/12/2014 → 14/12/2014
Sponsor	IEEE Nanjing Computational Intelligence Chapter, University of Bristol, Zhejiang Sci-Tech University, Zhejiang University

Navn	Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
Vol/bind	1

Bibliografisk note

Publisher Copyright:
© 2014 IEEE.

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10.1109/ISCID.2014.94

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Citationsformater

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title = "Analog circuit fault diagnosis based on DE-OS-ELM",

abstract = "Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.",

keywords = "analog circuits, differential evolution algorithm, online sequential learning machine",

author = "Shaowei Chen and Minhua Wu and Shuai Zhao",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 7th International Symposium on Computational Intelligence and Design, ISCID 2014 ; Conference date: 13-12-2014 Through 14-12-2014",

year = "2015",

month = mar,

day = "19",

doi = "10.1109/ISCID.2014.94",

language = "English",

series = "Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014",

pages = "509--513",

booktitle = "Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014",

publisher = "IEEE Signal Processing Society",

address = "United States",

}

Chen, S, Wu, M & Zhao, S 2015, Analog circuit fault diagnosis based on DE-OS-ELM. i Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014., 7064245, IEEE Signal Processing Society, Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, bind 1, s. 509-513, 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Hangzhou, Kina, 13/12/2014. https://doi.org/10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM. / Chen, Shaowei; Wu, Minhua; Zhao, Shuai.
Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014. IEEE Signal Processing Society, 2015. s. 509-513 7064245 (Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Bind 1).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Analog circuit fault diagnosis based on DE-OS-ELM

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AU - Wu, Minhua

AU - Zhao, Shuai

PY - 2015/3/19

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N2 - Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

AB - Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

KW - analog circuits

KW - differential evolution algorithm

KW - online sequential learning machine

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U2 - 10.1109/ISCID.2014.94

DO - 10.1109/ISCID.2014.94

M3 - Article in proceeding

AN - SCOPUS:84931059712

T3 - Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014

SP - 509

EP - 513

BT - Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014

PB - IEEE Signal Processing Society

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Y2 - 13 December 2014 through 14 December 2014

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Chen S, Wu M, Zhao S. Analog circuit fault diagnosis based on DE-OS-ELM. I Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014. IEEE Signal Processing Society. 2015. s. 509-513. 7064245. (Proceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014, Bind 1). doi: 10.1109/ISCID.2014.94

Analog circuit fault diagnosis based on DE-OS-ELM

Abstract

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