|Table of Contents|

[1] Chen Jingxu, Wang Wei, Chen Xuewu, Shen Jinshi, et al. Research on development of urban taxi supplybased on influence factors classification [J]. Journal of Southeast University (English Edition), 2013, 29 (2): 194-198. [doi:10.3969/j.issn.1003-7985.2013.02.015]
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Research on development of urban taxi supplybased on influence factors classification()
基于影响因素分类的城市出租车保有量发展规律
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
29
Issue:
2013 2
Page:
194-198
Research Field:
Traffic and Transportation Engineering
Publishing date:
2013-06-20

Info

Title:
Research on development of urban taxi supplybased on influence factors classification
基于影响因素分类的城市出租车保有量发展规律
Author(s):
Chen Jingxu Wang Wei Chen Xuewu Shen Jinshi
School of Transportation, Southeast University, Nanjing 210096, China
陈景旭 王炜 陈学武 沈劲石
东南大学交通学院, 南京 210096
Keywords:
taxi supply neural network model policy year influence factor
出租车保有量 神经网络模型 政策年份 影响因素
PACS:
U491
DOI:
10.3969/j.issn.1003-7985.2013.02.015
Abstract:
In order to determine the regulations of the development of taxi supply under entry regulations in Chinese cities, an improved neural network model is applied to find the particular years when the government artificially puts new taxis into the market, and then extract the political influence from the taxi supply. The model is also utilized to study the relationships between the adjusted taxi supply and non-policy factors. A case study of Nanjing city is conducted. The results show that 2001 and 2007 are the particular years that the Nanjing government artificially put new taxis into its taxi market, which is in accordance with the five-year plan of China and the local development plans. The results also show that the improved neural network model has a good performance in expositing the evolution of adjusted taxi supply related to non-policy factors.
为研究我国城市出租车保有量在准入规制条件下的发展规律, 应用改进的神经网络模型寻找政府人为投入出租车运力的年份, 并将政策因素的影响从出租车保有量中分离.继而研究调整后的出租车保有量与非政策性影响因素间的关系.以南京市为例进行建模分析, 结果表明2001年与2007年是南京市政府人为投放出租车运力的年份, 与中国五年计划及当地政府规划一致.与此同时, 实例所得出的结果显示改进的神经网络模型对揭示分离出政策影响后的出租车保有量随非政策性影响因素的发展规律有很高的精度.

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Memo

Memo:
Biographies: Chen Jingxu(1989—), male, graduate; Chen Xuewu(corresponding author), female, doctor, professor, chenxuewu@seu.edu.cn.
Foundation item: The National Basic Research Program of China(973 Program)(No.2012CB725400).
Citation: Chen Jingxu, Wang Wei, Chen Xuewu, et al. Research on development of urban taxi supply based on influence factors classification[J].Journal of Southeast University(English Edition), 2013, 29(2):194-198.[doi:10.3969/j.issn.1003-7985.2013.02.015]
Last Update: 2013-06-20