交通信息与安全Issue(1)：122-125,129,5.DOI:10.3963/j.issn1674-4861.2014.01.025
基于谱聚类的城市轨道站点分类方法
Using Spectral Clustering for Urban Rail Station Classification
摘要
Abstract
For the purpose of identifying the function and positioning of the urban rail stations and providing further guidance for design and construction ,a classification method using spectral clustering is established .On the basis of defi-ning the impact factors of urban rail station properties ,the data from Xi'an Metro Line 2 for the present and planned char-acteristics years are utilized to evaluate the effects of station classification .The K-means cluster algorithm and spectral cluster methods are employed ,including the unnormalized spectral clustering algorithm ,SM algorithm and NJW algo-rithm .The test results indicate that the NJW algorithm within the spectral clustering algorithm can properly classify the station according to the station properties under the influence of the urban rail network development and changes inland use and station properties .关键词
城市交通/站点分类/谱聚类/城市轨道站点/站点属性/数据挖掘Key words
urban traffic/stations classification/spectral clustering/urban rail stations/station properties/data mining分类
交通工程引用本文复制引用
余丽洁,李岩,陈宽民..基于谱聚类的城市轨道站点分类方法[J].交通信息与安全,2014,(1):122-125,129,5.基金项目
国家自然科学基金项目（批准号51208054）、中央高校基本科研业务费专项资金项目（批准号2013G1211005）资助 （）
