智能系统学报2016，Vol.11Issue(5)：586-593,8.DOI:10.11992/tis.201601024
基于度和聚类系数的中国航空网络重要性节点分析
Analysis of key nodes in China s aviation network based on the degree centrality indicator and clustering coefficient
摘要
Abstract
This paper determines the key nodes of China’ s aviation network based on degree centrality, closeness centrality,‘betweenness’ centrality, eigenvector centrality, semi⁃local centrality indicators, and then ranks these nodes in descending order of importance. Using a vulnerability index and reviewing risks from deliberate and ran⁃dom attack the effectiveness of the sorting methods is then evaluated. It is apparent from the corresponding vulnera⁃bility indices that the aviation network of China is most vulnerable to targeted attacks according to the betweenness centrality indicator. Moreover, based on the aviation network, this paper proposes a new evaluation method, which takes into account not only the number of neighbors, but also the clustering coefficient. Focusing on China’ s avia⁃tion network, the experimental results demonstrate that the evaluation accuracy of the new index ranks only second to the betweenness centrality, and is more efficient compared with betweenness centrality as regards time complexity.关键词
航空网络/节点重要性/度/聚类系数/复杂网络Key words
aviation network/key nodes/degree/clustering coefficient/complex network分类
自科综合引用本文复制引用
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):586-593,8.基金项目
国家自然科学基金项目（61573199）；天津自然科学基金项目（14JCYBJC18700）． （）
