• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus 收录
  • 全国中文核心期刊
  • 中国科技论文统计源期刊
  • 中国科学引文数据库来源期刊

航路网络关键节点识别方法研究

田文 方琴 周雪芳 宋津津

田文, 方琴, 周雪芳, 宋津津. 航路网络关键节点识别方法研究[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20220532
引用本文: 田文, 方琴, 周雪芳, 宋津津. 航路网络关键节点识别方法研究[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20220532
TIAN Wen, FANG Qin, ZHOU Xuefang, SONG Jinjin. Identification Method for Key Nodes in En-Route Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20220532
Citation: TIAN Wen, FANG Qin, ZHOU Xuefang, SONG Jinjin. Identification Method for Key Nodes in En-Route Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20220532

航路网络关键节点识别方法研究

doi: 10.3969/j.issn.0258-2724.20220532
基金项目: 国家重点研发计划(2021YFB1600500);国家自然科学基金项目(71971112);国家自然科学基金联合基金项目(U2033203);江苏省研究生创新计划项目(xcxjh20210710)
详细信息
    作者简介:

    田文(1981—),女,副教授,博士,研究方向为空中交通流量管理,E-mail:tianwen0665@qq.com

    通讯作者:

    田文(1981—),女,副教授,博士,研究方向为空中交通流量管理,E-mail:tianwen0665@qq.com

  • 中图分类号: V355.1

Identification Method for Key Nodes in En-Route Network

  • 摘要:

    有效辨识关键节点对增强网络韧性、提高运行能力具有重要现实意义,为提高航路网络关键节点识别的准确性,提出基于TOPSIS-灰色关联分析法的综合评价方法和航路网络节点分级方法. 首先,从复杂网络统计特性、交通流量特性、脆弱性三个方面构建航路网络关键节点评价指标体系;通过引入相对熵改进逼近理想值排序(technique for order preference by similarity to an ideal solution,TOPSIS)法,同时结合灰色关联分析法综合评价航路点重要程度,采用基于K-means聚类方法有效划分航路节点等级;最后,以民航空管实际运行数据为实例,开展关键节点识别. 研究表明:相较于单一指标,所建航路网络节点评价指标体系获得的评价结果更加全面;同时改进TOPSIS-灰色关联分析方法相较于传统TOPSIS法评价结果更加准确;本研究所提识别方法发现了我国华东地区典型繁忙航路网络中有29个关键节点,其在网络结构及交通流量方面起着较为关键的作用.

     

  • 图 1  邻接矩阵示意图

    Figure 1.  Adjacency matrix

    图 2  航路点重要程度综合评估流程

    Figure 2.  Comprehensive evaluation process of importance of en-route waypoints

    图 3  华东地区各航路点小时航班量变化情况

    Figure 3.  Changes in hourly flight volume at each en-route waypoint in Eastern China

    图 4  各指标对应权重

    Figure 4.  Weight corresponding to each index

    图 5  华东地区航路点的综合接近度

    Figure 5.  Comprehensive proximity of en-route waypoints in Eastern China

    图 6  聚类数判断

    Figure 6.  Judgment of number of clusters

    图 7  航路点重要程度分布

    Figure 7.  Importance distribution of en-route waypoints

    表  1  华东地区航路点评价指标规范化数值

    Table  1.   Normalized values of evaluation indexes for en-route waypoints in Eastern China

    航路点序号z11z12z13z14z21z22z23z31z32z33
    10.2220.0950.6100.0950.5330.3540.4470.0000.0970.897
    20.1110.0180.7940.0770.0000.0000.0000.0000.0680.831
    30.4440.1300.8710.1300.7330.4590.5050.0000.1340.789
    40.1110.3910.6910.0120.6670.0780.1070.0000.1300.838
    50.1110.1140.7650.0320.3330.1310.1840.0000.0890.835
    60.1110.0550.2510.0050.5330.1580.1750.5000.2420.869
    70.1110.0270.8470.0860.7330.2310.2430.0000.0850.850
    80.5560.6040.9240.1530.6000.2080.2520.0000.4070.892
    90.1110.1030.6130.0070.2000.0240.0580.0000.1290.811
    100.1110.0310.2850.0000.2670.0100.0290.0000.0610.840
    下载: 导出CSV

    表  2  航路网络排名前二十的评价结果

    Table  2.   Evaluation results of top 20 points in en-route network

    排名$ {G_i} $TOPSIS$ G_i^{'} $
    航路点航路点航路点
    10.703TOL0.867TOL0.697TOL
    20.685HFE0.759HFE0.603HFE
    30.639JTN0.724JTN0.593JTN
    40.620ELNEX0.729ELNEX0.495ELNEX
    50.603P2150.726P2150.500P215
    60.602SHR0.692SHR0.449SHR
    70.601DST0.699DST0.687DST
    80.588DO0.533DO0.641DO
    90.563BK0.608BK0.519BK
    100.561AND0.605AND0.412NOBEM
    110.559SHZ0.552SHZ0.617SHZ
    120.551KAKIS0.612KAKIS0.488BZ
    130.533NINAS0.541NINAS0.472LYG
    140.531LASAN0.533LASAN0.536SUPAR
    150.511UGAGO0.526UGAGO0.424UGAGO
    160.493SASAN0.509SASAN0.431YCH
    170.503PINOT0.497PINOT0.429RUPUD
    180.504P2630.509XUVGI0.433PK
    190.502JDZ0.498MADUK0.424OSIKI
    200.508BZ0.499OF0.612OF
    下载: 导出CSV
  • [1] NEWMAN M E J. The structure and function of complex networks[J]. SIAM Review, 2003, 45(2): 167-256. doi: 10.1137/S003614450342480
    [2] KITSAK M, GALLOS L K, HAVLIN S, et al. Identification of influential spreaders in complex networks[J]. Nature Physics, 2010, 6: 888-893. doi: 10.1038/nphys1746
    [3] CHEN D B, LÜ L Y, SHANG M S, et al. Identifying influential nodes in complex networks[J]. Physica A: Statistical Mechanics and Its Applications, 2012, 391(4): 1777-1787. doi: 10.1016/j.physa.2011.09.017
    [4] 闫玲玲,陈增强,张青. 基于度和聚类系数的中国航空网络重要性节点分析[J]. 智能系统学报,2016,11(5): 586-593.

    YAN Lingling, CHEN Zengqiang, ZHANG Qing. Analysis of key nodes in China s aviation network based on the degree centrality indicator and clustering coefficient[J]. CAAI Transactions on Intelligent Systems, 2016, 11(5): 586-593.
    [5] WANG H Y, SONG Z Q, WEN R Y, et al. Study on evolution characteristics of air traffic situation complexity based on complex network theory[J]. Aerospace Science and Technology, 2016, 58: 518-528. doi: 10.1016/j.ast.2016.09.016
    [6] BELKOURA S, COOK A, PEÑA J M, et al. On the multi-dimensionality and sampling of air transport networks[J]. Transportation Research Part E: Logistics and Transportation Review, 2016, 94: 95-109. doi: 10.1016/j.tre.2016.07.013
    [7] WANG H Y, XU X H, ZHAO Y F. Empirical analysis of aircraft clusters in air traffic situation networks[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2017, 231(9): 1718-1731. doi: 10.1177/0954410016660870
    [8] 任新惠,杨丽. 中国航空货运网络脆弱性分析[J]. 安全与环境学报,2020,20(3): 840-848.

    REN Xinhui, YANG Li. Vulnerability analysis of China air cargo transportation network[J]. Journal of Safety and Environment, 2020, 20(3): 840-848.
    [9] 徐开俊,肖成坤,杨泳,等. 基于复杂网络理论的中国城市航空网络有向加权分析[J]. 科学技术与工程,2021,21(36): 15669-15673.

    XU Kaijun, XIAO Chengkun, YANG Yong, et al. Directed Weighted Analysis of Chinese Urban Aviation Network Based on Complex Network Theory. Science Technology and Engineering[J], 2021, 21(36): 15669-15673.
    [10] BAE J, KIM S. Identifying and ranking influential spreaders in complex networks by neighborhood coreness[J]. Physica A Statistical Mechanics and Its Applications, 2014, 395: 549-559. doi: 10.1016/j.physa.2013.10.047
    [11] LIU Y, TANG M, ZHOU T, et al. Identify influential spreaders in complex networks, the role of neighborhood[J]. Physica A: Statistical Mechanics and Its Applications, 2016, 452: 289-298. doi: 10.1016/j.physa.2016.02.028
    [12] ZAOLI S, MAZZARISI P, LILLO F. Trip Centrality: walking on a temporal multiplex with non-instantaneous link travel time[J]. Scientific Reports, 2019, 9: 10570.1-10570.11.
    [13] ULLAH A, WANG B, SHENG J F, et al. Identification of nodes influence based on global structure model in complex networks[J]. Scientific Reports, 2021, 11: 6173.1-6173.11.
    [14] ULLAH A, WANG B, SHENG J F, et al. Identifying vital nodes from local and global perspectives in complex networks[J]. Expert Systems with Applications, 2021, 186: 115778.1-115778.10.
    [15] GUIMERÀ R, MOSSA S, TURTSCHI A, et al. The worldwide air transportation network: anomalous centrality, community structure, and cities' global roles[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(22): 7794-7799.
    [16] 段东立,战仁军. 基于相继故障信息的网络节点重要度演化机理分析[J]. 物理学报,2014,63(6): 385-393.

    DUAN Dongli, ZHAN Renjun. Evolution mechanism of no de imp ortance based on the information ab out cascading failures in complex networks[J]. Acta Physica Sinica, 2014, 63(6): 385-393.
    [17] MORONE F, MAKSE H A. Influence maximization in complex networks through optimal percolation[J]. Nature, 2015, 524: 65-68. doi: 10.1038/nature14604
    [18] 程光权,陆永中,张明星,等. 复杂网络节点重要度评估及网络脆弱性分析[J]. 国防科技大学学报,2017,39(1): 120-127.

    CHENG Guangquan, LU Yongzhong, ZHANG Mingxing, et al. Node importance evaluation and network vulnerability analysis on complex network[J]. Journal of National University of Defense Technology, 2017, 39(1): 120-127.
    [19] DU W B, ZHANG M Y, ZHANG Y, et al. Delay causality network in air transport systems[J]. Transportation Research Part E: Logistics and Transportation Review, 2018, 118: 466-476. doi: 10.1016/j.tre.2018.08.014
    [20] WANG Z K, WEN X X, WU M G. Identification of key nodes in aircraft state network based on complex network theory[J]. IEEE Access, 2019, 7: 60957-60967. doi: 10.1109/ACCESS.2019.2915508
    [21] 冯霞,贾宏璨. 考虑节点失效和边失效的航空网络鲁棒性[J]. 北京交通大学学报,2021,45(5): 84-92.

    FENG Xia, JIA Hongcan. Aviation network robustness considering node failure and edge failure[J]. Journal of Beijing Jiaotong University, 2021, 45(5): 84-92.
    [22] LORDAN O, SALLAN J M, SIMO P, et al. Robustness of the air transport network[J]. Transportation Research Part E: Logistics and Transportation Review, 2014, 68: 155-163. doi: 10.1016/j.tre.2014.05.011
    [23] CHEN Y, WANG J E, JIN F J. Robustness of China’s air transport network from 1975 to 2017[J]. Physica A: Statistical Mechanics and Its Applications, 2020, 539: 122876.1-122876.12.
    [24] LI W, CAI X. Statistical analysis of airport network of China[J]. Phys Rev E Stat Nonlin Soft Matter Phys, 2004, 69(4):046106.1-046106.11.
    [25] ZHOU Y M, WANG J W, HUANG G Q. Efficiency and robustness of weighted air transport networks[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 122: 14-26. doi: 10.1016/j.tre.2018.11.008
    [26] QI X Q, FULLER E, WU Q, et al. Laplacian centrality: a new centrality measure for weighted networks[J]. Information Sciences, 2012, 194: 240-253. doi: 10.1016/j.ins.2011.12.027
    [27] WANG N, GAO Y, HE J T, et al. Robustness evaluation of the air cargo network considering node importance and attack cost[J]. Reliability Engineering & System Safety, 2022, 217: 108026.1-108026.15.
    [28] 陈静,孙林夫. 复杂网络中节点重要度评估[J]. 西南交通大学学报,2009,44(3): 426-429. doi: 10.3969/j.issn.0258-2724.2009.03.021

    CHEN Jing, SUN Linfu. Evaluation of node importance in complex networks[J]. Journal of Southwest Jiaotong University, 2009, 44(3): 426-429. doi: 10.3969/j.issn.0258-2724.2009.03.021
    [29] 张喜平,李永树,刘刚,等. 节点重要度贡献的复杂网络节点重要度评估方法[J]. 复杂系统与复杂性科学,2014,11(3): 26-32,49.

    ZHANG Xiping, LI Yongshu, LIU Gang, et al. Evaluation method of importance for nodes in complex networks based on importance contribution[J]. Complex Systems and Complexity Science, 2014, 11(3): 26-32,49.
  • 加载中
图(7) / 表(2)
计量
  • 文章访问数:  12
  • HTML全文浏览量:  5
  • PDF下载量:  1
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-07-28
  • 修回日期:  2022-10-14
  • 网络出版日期:  2024-11-05

目录

    /

    返回文章
    返回