基于神经网络的城市交通流预测研究

Research of Urban Traffic Flow Forecasting Based on Neural Network

建立了一种基于神经网络的交通流量动态预测模型,分别采用BP神经网络和径向基网络(RBF)建立了预测模型,给出了数据预处理方法和预测模型评价指标.仿真结果表明该交通流量预测方法的有效性,结果分析得出径向基网络能够更加快速有效的进行城市交通流预测.

A dynamic traffic flow forecasting model based on neural network is proposed. BP and RBF neural network are used to build the forecasting models. The data pre-handle method and the judgment criterion of the forecasting model are given. Simulation shows the traffic flow forecasting method is effective, and the RBF can be more fast and effective in forecasting the traffic flow by simulation analysis.