计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (35): 203-205.DOI: 10.3778/j.issn.1002-8331.2008.35.061

• 工程与应用 • 上一篇    下一篇

基于粗糙集和支持向量机的高速公路事件检测

郭 倩,黄 林   

  1. 西北农林科技大学 信息工程学院,陕西 杨凌 712100
  • 收稿日期:2008-07-28 修回日期:2008-09-26 出版日期:2008-12-11 发布日期:2008-12-11
  • 通讯作者: 郭 倩

Freeway incident detection algorithm based on Rough Sets and Support Vector Machine

GUO Qian,HUANG Lin   

  1. Department of Information Engineering,Northwest Agriculture and Forest University,Yangling,Shaanxi 712100,China
  • Received:2008-07-28 Revised:2008-09-26 Online:2008-12-11 Published:2008-12-11
  • Contact: GUO Qian

摘要: 针对目前高速公路事件检测算法存在的局限性,提出基于粗糙集理论和支持向量机的高速公路事件检测算法。在介绍粗糙集理论和支持向量机原理的基础上,给出了检测算法的实现方法,并用Matlab对多种算法进行了仿真和性能对比。仿真结果表明,基于粗糙集理论和支持向量机的事件检测算法具有检测准确率高,训练时间短,泛化能力好等优点,具有良好的应用前景。

关键词: 粗糙集, 支持向量机, 高速公路, 事件检测

Abstract: Against of the limitations of current expressway incident detection algorithm,a traffic incident detection algorithm based on Rough Sets(RS) theory and Support Vector Machine(SVM) is proposed.On the basis of introducing the principle of Rough Sets theory and Support Vector Machine,the detection algorithm method is given.Further,variety of algorithms simulation and performance comparison is done with Matlab.Simulation results show that freeway incident detection algorithm based on RS and SVM has such advantages as high detection rate,fast training ability and good generalization.It is found to be potentially applicable in practice.

Key words: Rough Sets(RS), Support Vector Machine(SVM), freeway, incident detection