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

Dai Yuan Zhang; Jian Hui Zhan

doi:10.4028/www.scientific.net/AMM.513-517.695

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Short-Term Traffic Flow Forecasting of Road Based...

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

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

695-698

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.695

Citation:

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Online since:

February 2014

Authors:

Dai Yuan Zhang*, Jian Hui Zhan

Keywords:

Intelligent Transportation, Neural Network (NN), Short-Term Traffic Flow Forecasting, Spline, Spline Weight Function

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* - Corresponding Author

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