基于BP神经网络的城市交通流预测研究

Urban Traffic Volume Prediction Based on BP Neural Network

交通流预测在城市交通管理和控制中起着十分重要的作用。在分析城市交通流复杂非线性特性的基础上引入BP神经网络模型,从人工智能的角度对交通流预测进行了研究,同时给出了一种基于BP神经网络模型的交通流预测方法,通过对预测数据与实测数据的比较分析,证实了该方法的有效性。

Traffic volume prediction plays a very important role in urban traffic management and control. In this paper, BP neural network model is introduced and traffic volume prediction is studied from artificial intelligence theory based on the complex non - linear property of urban traffic volume. Meanwhile,a traffic volume prediction method based on BP neural network model is put forward. Case study proves the validity of the method by comparing and analyzing the prediction data and the real data.