[1]YAN Lingling,CHEN Zengqiang,ZHANG Qing.Analysis of key nodes in China’s aviation network basedon the degree centrality indicator and clustering coefficient[J].CAAI Transactions on Intelligent Systems,2016,11(5):586-593.[doi:10.11992/tis.201601024]
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Analysis of key nodes in China’s aviation network basedon the degree centrality indicator and clustering coefficient

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 5 Page number: 586-593 Column: 学术论文—智能系统 Public date: 2016-11-01
Title:
Analysis of key nodes in China’s aviation network basedon the degree centrality indicator and clustering coefficient
Author(s):
YAN Lingling1; 2;  CHEN Zengqiang1; 2; 3;  ZHANG Qing3
1. College of Computer and Control Engineering, Nankai University, Tianjin 300350, China;
2. Key Laboratory of Intelligent Robotics of Tianjin, Nankai University, Tianjin 300350, China;
3. College of Science, Civil Aviation University of China, Tianjin 300300, China
Keywords:
aviation network; key nodes; degree; clustering coefficient; complex network
CLC:
N94
DOI:
10.11992/tis.201601024
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 random attack the effectiveness of the sorting methods is then evaluated. It is apparent from the corresponding vulnerability 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 aviation 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.
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