SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis

Yang Sen; Song Xiao

doi:10.1109/ICEICT.2016.7879662

SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis

Yang Sen
, Song Xiao

School of Cyber Science and Technology

Ordnance Engineering College

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

1 Scopus citations

Abstract

Aiming at the problems of traditional classification methods, a SVM binary tree multi-classification method based on Improved Binary-coded quantum particle swarm optimization (IBQPSO) is proposed in this paper. First, IBQPSO algorithm and its steps are presented and multi-classification SVM based on binary tree is discussed. Then, the presented method and procedures are analyzed. Finally, taking the biquadratic filter circuit as an example to do the simulation experiment, the result shows that the proposed method is efficient.

Original language	English
Title of host publication	Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	107-110
Number of pages	4
ISBN (Electronic)	9781509007288
DOIs	https://doi.org/10.1109/ICEICT.2016.7879662
State	Published - 15 Mar 2017
Event	2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016 - Harbin, China Duration: 20 Aug 2016 → 22 Aug 2016

Publication series

Name	Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016

Conference

Conference	2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016
Country/Territory	China
City	Harbin
Period	20/08/16 → 22/08/16

Keywords

Analog circuit fault diagnosis
IBQPSO
SVM

Access to Document

10.1109/ICEICT.2016.7879662

Cite this

Sen, Y., & Xiao, S. (2017). SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis. In Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016 (pp. 107-110). Article 7879662 (Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICEICT.2016.7879662

Sen, Yang ; Xiao, Song. / SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis. Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 107-110 (Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016).

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title = "SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis",

abstract = "Aiming at the problems of traditional classification methods, a SVM binary tree multi-classification method based on Improved Binary-coded quantum particle swarm optimization (IBQPSO) is proposed in this paper. First, IBQPSO algorithm and its steps are presented and multi-classification SVM based on binary tree is discussed. Then, the presented method and procedures are analyzed. Finally, taking the biquadratic filter circuit as an example to do the simulation experiment, the result shows that the proposed method is efficient.",

keywords = "Analog circuit fault diagnosis, IBQPSO, SVM",

author = "Yang Sen and Song Xiao",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016 ; Conference date: 20-08-2016 Through 22-08-2016",

year = "2017",

month = mar,

day = "15",

doi = "10.1109/ICEICT.2016.7879662",

language = "英语",

series = "Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "107--110",

booktitle = "Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016",

address = "美国",

}

Sen, Y & Xiao, S 2017, SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis. in Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016., 7879662, Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016, Institute of Electrical and Electronics Engineers Inc., pp. 107-110, 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016, Harbin, China, 20/08/16. https://doi.org/10.1109/ICEICT.2016.7879662

SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis. / Sen, Yang; Xiao, Song.
Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 107-110 7879662 (Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016).

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

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AU - Sen, Yang

AU - Xiao, Song

PY - 2017/3/15

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N2 - Aiming at the problems of traditional classification methods, a SVM binary tree multi-classification method based on Improved Binary-coded quantum particle swarm optimization (IBQPSO) is proposed in this paper. First, IBQPSO algorithm and its steps are presented and multi-classification SVM based on binary tree is discussed. Then, the presented method and procedures are analyzed. Finally, taking the biquadratic filter circuit as an example to do the simulation experiment, the result shows that the proposed method is efficient.

AB - Aiming at the problems of traditional classification methods, a SVM binary tree multi-classification method based on Improved Binary-coded quantum particle swarm optimization (IBQPSO) is proposed in this paper. First, IBQPSO algorithm and its steps are presented and multi-classification SVM based on binary tree is discussed. Then, the presented method and procedures are analyzed. Finally, taking the biquadratic filter circuit as an example to do the simulation experiment, the result shows that the proposed method is efficient.

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KW - IBQPSO

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DO - 10.1109/ICEICT.2016.7879662

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BT - Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016

Y2 - 20 August 2016 through 22 August 2016

ER -

Sen Y, Xiao S. SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis. In Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 107-110. 7879662. (Proceedings of 2016 IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2016). doi: 10.1109/ICEICT.2016.7879662

SVM binary tree multi-classification method based on IBQPSO and its application in analog circuits fault diagnosis

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