分层PageRank算法和逆序系数在铁路网络中的应用  

The application of hierarchical PageRank algorithm and reverse order coefficient in railway network

作　　者：刘芝秀[1] 熊可 黄小杰[1] LIU Zhixiu;XIONG Ke;HUANG Xiaojie(Department of science,Nanchang Institute of technology,Nanchang Jiangxi 330099,China;School of Statistics,Jiangxi University of Finance and Economics,Nanchang Jiangxi 330077,China)

机构地区：[1]南昌工程学院理学院,江西南昌330099 [2]江西财经大学统计学院,江西南昌330077

出　　处：《南昌大学学报（理科版）》2021年第5期425-431,共7页Journal of Nanchang University(Natural Science)

基　　金：江西省教育厅科技项目(GJJ190963,GJJ180944);江西省高校人文社科课题(JY18233)。

摘　　要：提出便于并行计算的分层PageRank算法,用于计算我国城市列车站点的重要性,且引入了逆序系数的概念,用于度量城市列车站点的PageRank排名与城市GDP排名之间的差异,逆序系数越小两者排序的差异就越小。具体的数据实验表明城市列车站点的PageRank排名与城市GDP排名的逆序系数小于0.5,这说明PageRank排名与城市GDP排名近似,从而佐证了采用分层PageRank算法所计算的城市列车站点的PageRank值代表了其重要性。This paper presents a hierarchical PageRank algorithm for parallel computing,which is applied to calculate the importance of urban train stations in China.Furthermore,the concept of reverse order coefficient is given to describe the difference between PageRank ranking of urban train stations and urban GDP ranking.The smaller the reverse order coefficient is,the smaller difference between the two rankings has.Specific data experiments show that the reverse order coefficient between PageRank ranking of urban train stations and urban GDP ranking is less than 0.5,which shows that PageRank ranking is similar to urban GDP ranking.It demonstrates that the PageRank value of urban train station calculated by hierarchical PageRank algorithm represents its importance.

关 键 词：分层PageRank PAGERANK 逆序系数 逆序数 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]