Transport Modal Split of Commercial Sites Based on Artificial Neural Network - 文章详情页

作者：

ZHU, Yuehua (ZHU, Yuehua.) | CHEN, Yanyan (CHEN, Yanyan.) (学者：陈艳艳) | GENG, Xue (GENG, Xue.) | LIU, Lina (LIU, Lina.)

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摘要：

On　the　basis　of　the　characteristics　of　the　transport　mode　structure　at　commercial　sites,　this　paper　initially　analyzes　the　factors　that　have　influenced　public　transport　modal　split.　Taking　advantage　of　the　strong　nonlinear　mapping　and　generalization　characteristics　of　Back-Propagation　(BP)　neural　network,　a　prediction　model　of　public　transport　trip　proportion　is　established　based　on　investigation　data　of　commercial　sites　in　Beijing.　Meanwhile,　this　paper　makes　quantitative　analysis　of　the　factors　and　forecasts　public　transport　trip　proportion　at　commercial　sites　under　different　policies.　©　2008　China　Association　for　Science　and　Technology.

关键词：

Backpropagation Neural networks Predictive analytics Systems engineering

作者机构：

[ 1 ] [ZHU, Yuehua]Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, 100022, China
[ 2 ] [CHEN, Yanyan]Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, 100022, China
[ 3 ] [GENG, Xue]Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, 100022, China
[ 4 ] [LIU, Lina]Key Laboratory of Transportation Engineering, Beijing University of Technology, Beijing, 100022, China

通讯作者信息：

电子邮件地址：

cdyan@bjut.edu.cn

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