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

页码：695 / 698

页数：4

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