交通信息与安全2011，Vol.29Issue(5)：31-35,5.DOI:10.3963/j.ISSN1674-4861.2011.05.007
基于径向基函数神经网络的城市道路路段行程时间实时预测模型
A Real-time Travel Time Prediction Model Based on RBF Neural Network
摘要
Abstract
Travel time is a comprehensive index of traffic condition and the base of route guidance and traffic management. The prediction for travel time has been the key issue of ITS research. This paper provides a method to predict urban road travel time with Radial Basis Function Neural Network. Traffic data collected by loop and camera are used in simulation. The experiment results show the rationality of model. After comparison with BP neural network, the results prove that the RBF Neural network can predict the travel time in real time well and the adaptability and accuracy of RBF neural network are better than those of BP neural network.关键词
行程时间/神经网络/径向基函数Key words
travel time/ neural network/ Radial Basis Function分类
交通工程引用本文复制引用
刘江用,云美萍,闫亚文,杨晓光..基于径向基函数神经网络的城市道路路段行程时间实时预测模型[J].交通信息与安全,2011,29(5):31-35,5.基金项目
国家自然科学基金项目(批准号:70631002)资助 （批准号:70631002）
