Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (32): 223-225.DOI: 10.3778/j.issn.1002-8331.2008.32.067

• 工程与应用 • Previous Articles     Next Articles

Freeway incident detection based on Adaboost RBF neural network

YANG Tao1,ZHANG Liang-chun2   

  1. 1.Department of Transportation Engineering,Central South University,Changsha 410075,China
    2.Department of Information Science and Engineering,Central South University,Changsha 410075,China
  • Received:2007-12-04 Revised:2008-02-25 Online:2008-11-11 Published:2008-11-11
  • Contact: YANG Tao

基于Adaboost集成RBF神经网络的高速公路事件检测

杨 涛1,张良春2   

  1. 1.中南大学 交通运输工程学院,长沙 410075
    2.中南大学 信息科学与工程学院,长沙 410075
  • 通讯作者: 杨 涛

Abstract: A method based on Adaboost RBF neural network is proposed for freeway incident detection in this paper.By analyzing the principles of freeway incident detection and choosing the relative parameters,the topology of neural network is fixed.Then an algorithm utilizing Adaboost integrating RBF neural network for freeway incident detection and steps of its processing are presented.Finally,a simulation experiment is given.The result of the experiment shows that this algorithm can highly enhance the performance of RBF neural network (with high detection rate and low false alarm rate) and also has a good performance of generalization,which assesses the effectiveness of its application to freeway incident detection.

Key words: Adaboost, freeway incident detection, RBF neural network

摘要: 提出一种基于Adaboost集成RBF神经网络的高速公路事件检测方法。首先对高速公路事件检测原理进行分析,进行了相关的参数选择,确定了RBF神经网络的结构,然后采用改进的Adaboost方法集成RBF神经网络进行高速公路事件检测并给出了事件检测算法的步骤,最后进行了仿真实验,实验结果表明,该方法可以明显提高RBF神经网络性能(高检测率、低误报率),且具有较强的泛化能力,适宜高速公路事件检测。

关键词: Adaboost, 高速公路事件检测, RBF神经网络