Decision of the mechanical drive type with fuzzy characters based on the support vector machine

Hua Li Sun; Jian Ying Xie; Yao Feng Xue

Decision of the mechanical drive type with fuzzy characters based on the support vector machine

Hua Li Sun, Jian Ying Xie, Yao Feng Xue

Shanghai Jiao Tong University

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

4 Scopus citations

Abstract

An overview of the basic idea underlying support vector machine (SVM) is given, and then a multi-object classifier through one-against-all algorithm is formulated. A novel method of the support vector machines (SVMs) applied to the decision of mechanical drive type with fuzzy characters is discussed firstly. The results prove that SVM can provide a fast and effective method for engineering.

Original language	English
Title of host publication	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Pages	3170-3173
Number of pages	4
State	Published - 2004
Externally published	Yes
Event	Proceedings of 2004 International Conference on Machine Learning and Cybernetics - Shanghai, China Duration: 26 Aug 2004 → 29 Aug 2004

Publication series

Name	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume	5

Conference

Conference	Proceedings of 2004 International Conference on Machine Learning and Cybernetics
Country/Territory	China
City	Shanghai
Period	26/08/04 → 29/08/04

Keywords

Characteristic factors
Fuzzy membership function
Mechanical drive type
Multi-class classification
One-against-all algorithm
Support vector machines (SVMs)

Cite this

@inproceedings{7645e8a8d3984c388dd1b2ab8da4e4d0,

title = "Decision of the mechanical drive type with fuzzy characters based on the support vector machine",

abstract = "An overview of the basic idea underlying support vector machine (SVM) is given, and then a multi-object classifier through one-against-all algorithm is formulated. A novel method of the support vector machines (SVMs) applied to the decision of mechanical drive type with fuzzy characters is discussed firstly. The results prove that SVM can provide a fast and effective method for engineering.",

keywords = "Characteristic factors, Fuzzy membership function, Mechanical drive type, Multi-class classification, One-against-all algorithm, Support vector machines (SVMs)",

author = "Sun, \{Hua Li\} and Xie, \{Jian Ying\} and Xue, \{Yao Feng\}",

year = "2004",

language = "英语",

isbn = "0780384032",

series = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

pages = "3170--3173",

booktitle = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics",

note = "Proceedings of 2004 International Conference on Machine Learning and Cybernetics ; Conference date: 26-08-2004 Through 29-08-2004",

}

Sun, HL, Xie, JY & Xue, YF 2004, Decision of the mechanical drive type with fuzzy characters based on the support vector machine. in Proceedings of 2004 International Conference on Machine Learning and Cybernetics. Proceedings of 2004 International Conference on Machine Learning and Cybernetics, vol. 5, pp. 3170-3173, Proceedings of 2004 International Conference on Machine Learning and Cybernetics, Shanghai, China, 26/08/04.

Decision of the mechanical drive type with fuzzy characters based on the support vector machine. / Sun, Hua Li; Xie, Jian Ying; Xue, Yao Feng.
Proceedings of 2004 International Conference on Machine Learning and Cybernetics. 2004. p. 3170-3173 (Proceedings of 2004 International Conference on Machine Learning and Cybernetics; Vol. 5).

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

TY - GEN

T1 - Decision of the mechanical drive type with fuzzy characters based on the support vector machine

AU - Sun, Hua Li

AU - Xie, Jian Ying

AU - Xue, Yao Feng

PY - 2004

Y1 - 2004

N2 - An overview of the basic idea underlying support vector machine (SVM) is given, and then a multi-object classifier through one-against-all algorithm is formulated. A novel method of the support vector machines (SVMs) applied to the decision of mechanical drive type with fuzzy characters is discussed firstly. The results prove that SVM can provide a fast and effective method for engineering.

AB - An overview of the basic idea underlying support vector machine (SVM) is given, and then a multi-object classifier through one-against-all algorithm is formulated. A novel method of the support vector machines (SVMs) applied to the decision of mechanical drive type with fuzzy characters is discussed firstly. The results prove that SVM can provide a fast and effective method for engineering.

KW - Characteristic factors

KW - Fuzzy membership function

KW - Mechanical drive type

KW - Multi-class classification

KW - One-against-all algorithm

KW - Support vector machines (SVMs)

UR - https://www.scopus.com/pages/publications/6344280395

M3 - 会议稿件

AN - SCOPUS:6344280395

SN - 0780384032

T3 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

SP - 3170

EP - 3173

BT - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

T2 - Proceedings of 2004 International Conference on Machine Learning and Cybernetics

Y2 - 26 August 2004 through 29 August 2004

ER -

Decision of the mechanical drive type with fuzzy characters based on the support vector machine

Abstract

Publication series

Conference

Keywords

Other files and links

Fingerprint

Cite this