Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 321-325.doi: 10.11896/jsjkx.200900112

• Intelligent Computing • Previous Articles     Next Articles

Analysis and Application of Global Aviation Network Structure Based on Complex Network

HU Jun1, WANG Yu-tong2, HE Xin-wei2, WU Hui-dong2, LI Hui-jia3   

  1. 1 School of Economics and Management,Fuzhou University,Fuzhou 350108,China
    2 School of Management Science and Engineering,Central University of Finance and Economics,Beijing 100081,China
    3 School of Science,Beijing University of Posts and Telecommunications,Beijing 100876,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:HU Jun,born in 1993,Ph.D candidate.His main research interests include complex network,cluster,social network,and control theory.
    LI Hui-jia,born in 1985,Ph.D,professor.His main research interests include data mining,pattern recognition,complex network,and control theory.
  • Supported by:
    National Natural Science Foundation of China(71871233,71701049,717871159) and Fundamental Research Funds for the Central Universities of China (2020XD-A01-1).

Abstract: With the continuous expansion of domestic and international trade activities,the economic and social value of air transportation are constantly improved.As the carrier of air transport,the empirical study and analysis of aviation network is of great significance.Based on the global flight information,this paper analyzes the global aviation network with the help of complex network,and finds that the global aviation network is a scale-free small-world network,whose degree distribution is power law distribution.Through fitting,it is found that the number of points between the number and degree is mainly exponential,but with the increase of degree,the number of points between the number and degree is mainly linear,and the clustering coefficient tends to be stable with the increase of degree.In addition,this paper finds that the global aviation network has obvious regional clustering effect through the community partition algorithm.

Key words: Aviation network, Community division, Complex network, Small world network

CLC Number: 

  • TP393
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