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由于不同管制目标下的城市客运出租汽车数量管制绩效存在差异，为掌握省会城市客运出租汽车数量管制强度，将人口拥有率、建成区面积拥有率、公交客运量比率、GDP拥有率、道路面积拥有率和对外客运量比率作为分类指标，运用模糊-均值聚类法对中国省会城市客运出租汽车的数量管制强度进行分类，进行Matlab 7.0编程，经聚类有效性分析和F-统计量检验后获得最佳分类方案.结果表明，将31个样本城市的客运出租汽车数量管制强度分为低、较低、中、较高、高5个等级最佳，分类结果为建立出租汽车数量调控模型奠定了基础.

Clustering Taxi Quantity Regulatory Levels of Chinese Capital Cities

Different purposes of taxi quantity control lead to different performances of quantity regulation in Chinese urban areas.To obtain a clear division of taxi quantity regulation levels of Chinese capital cities,a fuzzy c-means clustering is presented.The paper identifies six important demanding factors such as population,urban built-up area,transit volume,GDP,road area and amount of intercity passenger to get the corresponding indexes of urban taxi quantity regulatory levels.An effecient classification scheme is selected with clustering effectiveness analysis and F-statistics test after running a dedicated the MATLAB 7.0 program.The result indicates that thirty-one capital cities of mainland China are definitely classified into five categories.The categorization of quantity regulatory levels in this paper provide references for formulating the of taxi license supply models.