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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.
In order to study the law of the development of urban taxi ownership in China under the access regulation, this paper applies the improved neural network model to find out the year of government man-made taxi investment and separates the influence of policy factors from the number of taxi ownership. The relationship between adjusted taxi ownership and non-policy influencing factors.Taking Nanjing as an example, the results of modeling show that 2001 and 2007 are the years when Nanjing municipal government manned taxi capacity and compared with five years in China Plan and local government plan.At the same time, the result of the example shows that the improved neural network model has a high precision to reveal the law of the non-policy influencing factors of the taxi ownership after the influence of the policy is separated.