Prediction for Percentage of Vehicle Entering Expressway Rest Area Based on BP Neural Network

In order to scientifically decide the percentage of vehicle entering expressway rest area, based on analyzing the influencing factors relating to the percent of mainline traffic stopping, a BP neural network prediction model for it was put forward. Finally, The Xinzheng Rest Area (XRA) was taken as...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 178-181; pp. 1956 - 1960
Main Authors Liu, Jia, Shen, Xiao Yan, Liu, Hao Xue
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.05.2012
Subjects
Percentage of Vehicle Entering Expressway Rest Area
Expressway
Rest Area
BP Neural Network (BPNN)
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Summary:In order to scientifically decide the percentage of vehicle entering expressway rest area, based on analyzing the influencing factors relating to the percent of mainline traffic stopping, a BP neural network prediction model for it was put forward. Finally, The Xinzheng Rest Area (XRA) was taken as an example for verifying the feasibility of the prediction model and determining the influence degree of the Shijiazhuang-Wuhan high-speed railway on the percentage of mainline vehicles entering XRA. The result shows that the model had a high precision and reliability.
Bibliography:Selected, peer reviewed papers from the 2nd International Conference on Civil Engineering, Architecture and Building Materials (CEABM 2012), May 25-27, 2012, Yantai, China
ISBN:3037854243
9783037854242
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.178-181.1956