基于人工神经网络城市交通流量智能预测的研究

通过对我国目前城市交通情况的分析．说明交通拥挤和流量大小息息相关，因此对城市交通流量进行预测具有重要的意义。目前应用于城市交通流量智能预测的人工神经网络模型主要有线性网络、BP网络、反馈网络等。经过综合分析而采用了线性网络对城市交通流量进行预测，其优点主要表现在结构简单，实用方便，反应速度快，实时性强。根据城市交通的具体情况，对城市交通流量的预测模型进行了仿真。其仿真结果表明所采用的线性神经网络能够用于城市交通流量的预测。

Research on urban traffic flow lntelligent prediction based on artificial neural network

By analying the current situation of the urban traffic system,this paper expounds the relationship between traffic congestion and the traffic flow,and shows that it's very important to make the traffic flow prediction of the urban traffic system. Nowadays, some types of artificial neural network models are used in the urban traffic flow prediction, such as linear network, back propagation and feedback network. In this paper, the linear network model is mainly used to analyze the traffic flow prediction, which is simple in the construction, easy in the application, quick in the response and strong in the real time. The urban traffic flow prediction is simulated under the particular situation,and the result of the simulation shows that the Linear Network shown in this paper can fit the urban traffic flow prediction very well.