Study on the fault of power-shift steering transmission based on SVM structural risk

Ying Feng Zhang*, Ma Biao, Chang Song Zheng, Jin Le Zhang

*Corresponding author for this work

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

Abstract

Support vector machine (SVM) is an efficient method for data mining of oil analysis. The principle and structural risk of SVM are described in this paper. And the structural risk is studied using oil analysis data. During the process, parameters determination is a very important part because parameters have great influence on the performance of SVM. We select the Radial Basis Function (RBF) as the kernel function of SVM and study the influence of parameters sand C for SVM structural risk. The recognition rate of SVM model is influenced by SVM structural risk. The recognition rate is studied through an experimentation research.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Pages3045-3049
Number of pages5
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China
Duration: 9 Aug 200912 Aug 2009

Publication series

Name2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

Conference

Conference2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Country/TerritoryChina
CityChangchun
Period9/08/0912/08/09

Keywords

  • Power-shift steering transmission
  • SVM
  • Structural risk

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