摘要
为明确城市轨道站点的功能与定位,以对站点的设计与建设提供指导,建立了基于谱聚类算法的城市轨道站点分类方法。在确立影响轨道站点属性因素参数的基础上,应用西安地铁2号线现状及规划特征年的数据分别对快速聚类法及非规格化谱聚类算法、SM算法、NJW算法等谱聚类算法的站点分类效果进行评述。结果显示谱聚类算法中的NJW算法,能够抓住站点的特征进行分类,且能准确反映随着轨道线网和城市发展,站点特性的变化。
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＆#39;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 .
出处
《交通信息与安全》
2014年第1期122-125,129,共5页
Journal of Transport Information and Safety
基金
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
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
urban traffic
stations classification
spectral clustering
urban rail stations
station properties
data mining
