基于异常移动网络的地铁大客流演化研究  

Research on Evolution of Large Passenger Flow in Urban Metro Based on Anomalous Mobility Network

作　　者：王璞[1,2] 周梦楠[1,2] 黄智仁 WANG Pu;ZHOU Meng-nan;HUANG Zhi-ren(School of Traffic and Transportation Engineering,Central South University,Changsha,410075;Rail Data Research and Application Key Laboratory of Hunan Province,Central South University,Changsha,410075)

机构地区：[1]中南大学交通运输工程学院,长沙410075 [2]中南大学轨道交通大数据湖南省重点实验室,长沙410075

出　　处：《电子科技大学学报》2020年第5期732-738,共7页Journal of University of Electronic Science and Technology of China

基　　金：国家重点研发计划(2016YFB1200401);国家自然科学基金面上项目(71871224)。

摘　　要：为了揭示城市轨道交通大客流的演化机制,该文引入了异常移动网络的概念,并利用复杂网络分析技术,对比研究了深圳地铁正常客流和大客流状态下异常移动网络的结构复杂性和动态演变过程;提出了能有效识别异常移动网络关键节点的指标。研究结果表明,随着大客流的集聚和疏散,异常移动网络呈现从入度“长尾”到出度“长尾”的演变,网络结构在无标度网络与随机网络间转换。研究结论可为地铁大客流预警、制定客流组织管理方案提供参考依据。In order to reveal the evolutionary mechanism of large passenger flow in urban metro,this paper introduces the concept of anomalous mobility network.Complex network analysis is used to study the structural complexity and dynamic evolution of anomalous mobility networks under ordinary and large passenger flow situations in Shenzhen metro.In addition,this paper proposes an indicator to identify the key nodes of anomalous mobility network.Results show that the anomalous mobility network evolves from long-tailed indegree to longtailed outdegree with the aggregation and the evacuation of passenger flows.There is a transition process between the scale-free network and the random network.This research can provide a reference for early warning of large passenger flow,passenger flow organization and management in urban metro.

关 键 词：异常移动网络 复杂网络 关键节点 地铁客流 网络演化 

分 类 号：TP301[自动化与计算机技术—计算机系统结构] U491[自动化与计算机技术—计算机科学与技术]