| 基于RBF的城市快速路交通异常事件自动检测算法分析 |
| |
| 引用本文： | 张秀红,陈力,胡刚.基于RBF的城市快速路交通异常事件自动检测算法分析[J].交通科技与经济,2011,13(2):5-8,13. |
| |
| 作者姓名： | 张秀红 陈力 胡刚 |
| |
| 作者单位： | 1. 广东工业大学,机电工程学院,广东广州510006
2. 广东工业大学自动化学院,广东广州,510006 |
| |
| 基金项目： | 广东省科技计划项目(2009B010800052) |
| |
| 摘 要： | 通过对城市快速路交通异常事件自动检测方法的分析,提出用MATLAB神经网络工具箱建立交通异常事件自动检测RBF模型,并通过采集的实测交通异常事件数据对RBF神经网络在自动检测算法中进行仿真研究。结果表明RBF神经网络算法具有检测率高、误报率低和检测速度快等优点。
|
| 关 键 词： | 城市快速路 交通异常事件 自动检测 RBF神经网络 |
Analysis on Radial Basis Function for Urban Expressway of Automatic Traffic Incidents Detection Algorithm |
| |
| ZHANG Xiu-hong,CHEN Li,HU Gang.Analysis on Radial Basis Function for Urban Expressway of Automatic Traffic Incidents Detection Algorithm[J].Technology & Economy in Areas of Communications,2011,13(2):5-8,13. |
| |
| Authors: | ZHANG Xiu-hong CHEN Li HU Gang |
| |
| Institution: | ZHANG Xiu-hong1,CHEN Li2,HU Gang2(1.Guangdong University of Technology,Mechanical and Electrical Engineering College Guangzhou 510006,China,2.Guangdong University of Technology,Automation College,Guangzhou 510006,China) |
| |
| Abstract: | After analyzing the method of automatic detection on traffic abnormal incidents for urban expressway,this paper established a RBF neural network model based on MATLAB neural network toolbox.Then through using the field traffic incidents date,the radial basis function(RBF)neural network algorithm applied and researched on automatic incident detection.Simulation result shows its advantages,such as its higher detection rate,lower false alarm rate and shorter mean detection time. |
| |
| Keywords: | urban expressway traffic abnormal incidents automatic detection RBF(Radial Basis Function)neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
