改进BP神经网络在预测城市交通流量中的应用

The City Traffic Flow Prediction Based on Modified BP Neural Network

预测交通流量是动态交通控制的前提。该文提出基于改进BP算法的交通流动态时序的预测算法,对交通流量数据进行分析和研究,以动态交通控制理论为基础,应用MATLAB软件建立交通流量预测模型。并通过实验仿真验证把改进BP神经网络(BP NN)用于建设智能交通体系成为了一种非常明智的选择。

Short-term traffic flow prediction is the basis of dynamic traffic control and guidance, a new Tra- ffic Patten identification model is proposed which is based on Modified BP Neural Network, The paper ba- se on dynamic traffic control theory and analysis traffic flow data. use neural network and MATLAB software to build the prediction model of short-term traffic flow. The simulation results indicate that apply BP Neural Network to traffic field is an intelligent choice.