文章基本信息

标题：Vehicle Classification Method Based on Single-Point Magnetic Sensor
本地全文：下载
作者：Yao He ; Yao He ; Yuchuan Du 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2012
卷号：43
页码：618-627
DOI：10.1016/j.sbspro.2012.04.135
语种：English
出版社：Elsevier
摘要：AbstractIn this paper a novel and scientific vehicle classification method is proposed, which is used on a new single-point magnetic sensor. The original waveform is transformed into numerical format by the data fusion technology for feature extraction. The extracted feature subsets are evaluated by Filter-Filter-Wrapper model, and then the nonredundant feature subset which fully reflects the difference of various vehicle types and is adaptable to the vehicle classifier is determined. On the basis of the optimal feature subset, this paper provides a novel vehicle classification algorithm based on Clustering Support Vector Machines(C-SVM). Particle Swarm Optimization (PSO) is used to search the optimal kernel parameter and slack penalty parameter. The cross-validation result of 460 samples shows that the classification rate of proposed vehicle classification method is better than 99%. It demonstrates that the vehicle classification method would be able to enhance efficiency of data mining, capability of machine learning and accuracy of vehicle classification.
关键词：Magnetic sensor;Vehicle classification;Feature selection;RelifF;PSO;C-SVM