基于神经网络及相似日的城市交通流量预测模型研究

Traffic Flow Forecasting Model Based on Neurual Network and Similar Day Principle

针对智能运输交通系统中的交通流量预测问题,提出了采用基于神经网络及相似日的交通流量预测模型。城市交通流量受到道路本身的通行能力、工作日与节假日、雨雪雾天气等因素的影响。由于相似条件下的交通流量具有较大的关联性,基于差异性和相关性原理,提出了基于相似日和神经网络的城市交通流量预测模型。以实际交通数据进行实验仿真,结果证明本文提出的预测模型具有较好的误差精度,具有实用性。

In order to solve the traffic flow forecasting problem in intelligent traffic system,this paper proposes a prediction model of traffic flow based on neural network and similar day principle.Urban traffic is affected by traffic capacity of the road,working days or holidays,snow and fog weather.The influence of such factors as due to the similar conditions of traffic flow has great relevance.This paper introduces a model based on similar day principle and neural network.