交通信息与安全2011，Vol.29Issue(3)：79-83,5.DOI:10.3963/j.ISSN 1674-4861.2011.03.019
基于BP神经网络的微观交通安全预测方法
A Microcosmic Forecasting Model for Traffic Safety Based on BP Neural Network
摘要
Abstract
The principal component analysis and BP neural network were introduced into the prediction of traffic safety. Factors influencing traffic accidents were analyzed from microcosmic perspective. The road parameters were analyzed and the original data were obtained. The obtained data were then analyzed by principal component analysis, which later would be used as the input of BP neural network to predict the traffic safety. The result shows that the BP neural network based on principal component analysis has a higher accuracy than general BP neural network. Furthermore, the impact of road parameters on traffic accidents from the microcosmic perspective is achieved.关键词
主成分分析/BP神经网络/道路安全性预测Key words
principal component analysis/ BP neural network/ prediction of road safety分类
交通工程引用本文复制引用
康迪,马寿峰,钟石泉..基于BP神经网络的微观交通安全预测方法[J].交通信息与安全,2011,29(3):79-83,5.基金项目
国家自然科学基金项目(批准号:50908155)资助 （批准号:50908155）
