Short-Term Traffic Flow Forecasting of Road based on Spline Weight Function Neural Networks

被引:0
|
作者
Zhang, Daiyuan [1 ]
Zhan, Jianhui [1 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Comp, Nanjing 210003, Jiangsu, Peoples R China
来源
APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY | 2014年 / 513-517卷
关键词
Neural Network; Spline; Spline Weight Function; Intelligent Transportation; Short-Term Traffic Flow Forecasting;
D O I
10.4028/www.scientific.net/AMM.513-517.695
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Traditional short-term traffic flow forecasting of road usually based on back propagation neural network, which has a low prediction accuracy and convergence speed. This paper introduces a spline weight function neural networks which has a feature that the weight function can well reflect sample information after training, thus propose a short-term traffic flow forecasting method base on the spline weight function neural network, specify the network learning algorithm, and make a comparative tests bases on the actual data. The result proves that in short-term traffic flow forecasting, the spline weight function neural network is more effective than traditional methods.
引用
收藏
页码:695 / 698
页数:4
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