期刊文献+

中国民用航空网络的中心化及节点攻击比较 被引量:5

Centrality of China aviation network and node attack comparison
下载PDF
导出
摘要 以中国民用航空(CAN)网络为研究对象,应用度、紧密度、点介数和流介数四个指标对CAN进行中心化处理,判断最合适的处理方法并认定CAN网络的主要节点.其中,点介数指标对CAN网络的中心化处理效果最好,中心化程度达到96.92%.最后得出结论,中国航空网络的前五中心节点按顺序分别是北京、上海、广州、乌鲁木齐、昆明.进一步地,采用节点攻击的方法进行了验证. This paper chooses China aviation network(CAN) as its research objective, applying respectively the four indexes of centrality degree, closeness, betweenness and flow betweenness to the centrality of CAN, thereafter determining the most appropriate treatment and thus identifying the primary nodes of CAN. It has been found that among the four kinds of treatment results, betweenness, up to 96.92% in centrality, is the best index for the centrality of CAN. The finding leads to a conclusion that the top five central nodes of CAN are Beijing, Shanghai, Guangzhou, Urumqi and Kunming in order, which has been further verified by the node attack method.
作者 崔博
出处 《系统工程学报》 CSCD 北大核心 2013年第1期1-7,共7页 Journal of Systems Engineering
基金 国家自然科学基金资助项目(71171111)
关键词 社会网络 中国航空网络(CAN) 中心化 介数 social network China aviation network centrality betweenness
  • 相关文献

参考文献21

  • 1Guimera R, Amaral L A N. Modeling the world-wide airport network[J]. The European Physical Journal B, 2004, 38(2): 381-385.
  • 2Guimera 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.
  • 3Barrat A, Barthelemy M, Pastor-Satorras R, et al. The architecture of complex weighted networks[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101(11): 3747-3752.
  • 4Barrat A, Barthelemy M, Vespignani A. The effects of spatial constraints on the evolution of weighted complex networks[J]. Journal of Statistical Mechanics: Theory and Experiment, 2005, 2005(5): 05003.
  • 5Colizza V, Barrat A, Barthelemy M, et al. The role of the airline transportation network in the prediction and predictability of global epidemics[J]. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103(7): 2015-2020.
  • 6Li W, Cai X. Statistical analysis of airport network of China[J]. Physical Review E, 2004, 69(4): 6106-6112.
  • 7Jordan C. Sur les assemblages des lignes[J]. Journal Fur Die Reine Und Angewandte Mathematik, 2009, 1869(70): 185-190.
  • 8Gaertler M, Wagner D. Algorithms for representing network centrality, groups and density and clustered graph representation [J]. Coevolution and Self-Organization in Dynaraical Networks, 2001, 3(1): 1-7.
  • 9Porta S, Crucitti P, Latora V. The network analysis of urban streets: A dual approach [J]. Physica A: Statistical Mechanics and its Applications, 2006, 369(2): 853-866.
  • 10王法辉,金凤君,曾光.中国航空客运网络的空间演化模式研究[J].地理科学,2003,23(5):519-525. 被引量:101

二级参考文献82

共引文献234

同被引文献84

引证文献5

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部