A New SVM Algorithm and AMR Sensor Based Vehicle Classification

摘要：

This paper proposes a new and efficient vehicle classification system base on support vector machine (SVM) algorithm and anisotropic magnetoresistive (AMR) sensor. The main point is that the AMR sensors detect the change of earth magnetic field which will be disturbed differently by different types of passing traffic vehicle. The characteristics of AMR sensor output model of the sample data, SVM learning classification algorithm, kernel function and model parameters are analyzed in detail. The results of our experiments show that this vehicle classification system base on AMR sensor and SVM algorithm is effective and efficient.

关键词： SVM Vehicle Classification AMR Sensor

作者: Zhou Feng Wang Mingzhe

作者单位: Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan, 430074,China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 1373-1377

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）