关键词: 交通流预测, 多尺度分析, 神经网络, 仿真

Abstract: Aiming at characteristics of nonlinearity, strong interference and no obvious regularity of traffic flow caused by the complexity and uncertainty of time variance in current traffic system, a new approach is proposed for traffic flow prediction. Firstly, the traffic flow sequence made of different frequencies is decomposed into low and high frequencies in the multi-resolution analysis and the trend components are restored according to the reconstructing principle of wavelet coefficients. Secondly, the artificial neural network is used to forecast these coefficients respectively. Finally, the real detecting traffic data are used to testify the precision of the model.The results show that the forecast model based on multi-scale analysis and neural network has higher accuracy than the traditional artificial neural network model does, and this new model can be used in the dynamic forecast of traffic flow in real time.

Key words: traffic flow prediction, multi-scale analysis, artificial neural network, simulation