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

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

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.

源语言英语
主期刊名2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
3045-3049
页数5
DOI
出版状态已出版 - 2009
活动2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, 中国
期限: 9 8月 200912 8月 2009

出版系列

姓名2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

会议

会议2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
国家/地区中国
Changchun
时期9/08/0912/08/09

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