摘要： 针对城市公共自行车系统快速发展面临的潮汐问题,提出一种基于SimRank的自行车站点聚类算法。从站点间的关联关系出发,基于站点特性定义站点相似度,引入SimRank算法进行站点相似度计算,并按计算得到的相似度值,根据最大相似优先的思想对站点进行聚类。实验结果表明,该算法得到的聚类结果能准确反映自行车流趋势和区域特征,其中同聚类成员也具有较大的关联性。

关键词: 公共自行车, 聚类分析, 站点联系, 站点特征, 相似度矩阵

Abstract: In view of the tide problem of fast developed city public bike system,this paper proposes a station clustering algorithm based on SimRank,which uses the characteristics of public bike.Firstly,the definition of station similarity is proposed based on the relation between stations.Secondly,the SimRank algorithm is introduced to calculate the similarity between stations.Finally,according to the calculated similarity values,the stations are clustered with the idea of maximum similarity priority.Experimental results show that the clustering results by the proposed algorithm have accurate bike flow characteristic and regional characteristic,meanwhile,the members in same cluster have great relevance.

Key words: public bike, clustering analysis, station relationship, station feature, similarity matrix

中图分类号: 

• TP391