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

  • Hua Li Sun*
  • , Jian Ying Xie
  • , Yao Feng Xue
  • *Corresponding author for this work
  • Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationProceedings of 2004 International Conference on Machine Learning and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3170-3173
Number of pages4
ISBN (Print)0780384032, 9780780384033
DOIs
StatePublished - 2004
Externally publishedYes
Event3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004 - Shanghai, China
Duration: 26 Aug 200429 Aug 2004

Publication series

NameProceedings of 2004 International Conference on Machine Learning and Cybernetics
Volume5

Conference

Conference3rd International Conference on Machine Learning and Cybernetics, ICMLC 2004
Country/TerritoryChina
CityShanghai
Period26/08/0429/08/04

Keywords

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

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