公共自行车系统的租赁点聚类与功能识别

Rental Points Clustering and Function Identification of Public Bicycle System

租赁点功能识别对公共自行车系统的平衡调度和布局规划具有重要作用,而系统中积累的大量历史数据可反映用户在不同时间和地点的社会经济活动,并且与租赁点功能紧密联系。为此,对系统历史数据进行分析,构建公共自行车系统租赁点聚类模型。结合租赁点的时空属性,利用潜在狄利克雷分布模型挖掘租赁点的功能特征,使用K-means聚类算法进行特征聚类。通过集群模式特征分析并使用兴趣点数据和租赁点名称信息对聚类结果进行验证,结果表明,该模型可以有效地辅助系统管理者掌握公共自行车系统租赁点的功能分布。

The function identification of Public Bicycle System（PBS） plays an important role for the balancing scheduling and layout planning of the system. As a new public transport mode,PBS has accumulated more and more data,which not only can reflect the social and economic activities of users at different times and locations,but also has a close connection with the function of the rental points. By combining the spate-time attributes of the leased point and through the historical data analysis of the system ,this paper constructs a rental points clustering model of public bicycle system. It makes use of the Latent Dirichlet Allocation（LDA） model and K-means clustering algorithm to find the functional areas of the system,and through the analysis of the clusters＇ use features and uses Point of Interest （POI） data and station names to verify the results. The results show that the proposed model can help the system managers grasp the function distribution of the rental 19oints in PBS.