基于BP神经网络的动态交通流量预测

Forecast of Dynamical Traffic Flows Baseed on BP Artificial Neural Network

本文通过对BP神经网络和影响交通流量因素的分析,采用Windrow-Hoff学习算法、Kolmogorov定理和trainlm训练方法,实现对长春市开运街和湖西路路段动态交通流量的预测.

The thesis analyzes BP artificial neural network and factors of affecting traffic flows,adopts algorithm of Windrow-Hoff learning,theory of Kolmogorov and drill of Trainlm,realizes the forecast of dynamical traffic flows on Kaiyun street and Huxi road in Changchun.