摘要
基于BP神经网络和RBF神经网络构建了城市环路交通流动态实时预测模型,并对北京市三环路的实测交通流数据进行了预测分析.实证结果表明,该模型具有较高的精确度,算法的动态实时性也满足实际预测系统的要求,具有较好的实用性.
Based on BP neural network and RBF neural network, this paper formed a model of urban ring road traffic flow dynamic real-time forecast, and it makes predictions and analysis for the real traffic flow data of the 3er ring road in Beijing to test the validity of the model. The result of the experiment shows that this model has high accuracy. The real-time feature of the algorithm can satisfy the practical forecast system.
出处
《交通运输系统工程与信息》
EI
CSCD
2006年第4期13-17,共5页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(70171058).
