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Structural properties of the Chinese air transportation multilayer network

Author

Listed:
  • Hong, Chen
  • Zhang, Jun
  • Cao, Xian-Bin
  • Du, Wen-Bo

Abstract

Recently multilayer networks are attracting great attention because the properties of many real-world systems cannot be well understood without considering their different layers. In this paper, we investigate the structural properties of the Chinese air transportation multilayer network (ATMN) by progressively merging layers together, where each commercial airline (company) defines a layer. The results show that the high clustering coefficient, short characteristic path length and large collection of reachable destinations of the Chinese ATMN can only emerge when several layers are merged together. Moreover, we compare two main types of layers corresponding to major and low-cost airlines. It is found that the small-world property and the rich-club effect of the Chinese ATMN are mainly caused by those layers corresponding to major airlines. Our work will highlight a better understanding of the Chinese air transportation network.

Suggested Citation

  • Hong, Chen & Zhang, Jun & Cao, Xian-Bin & Du, Wen-Bo, 2016. "Structural properties of the Chinese air transportation multilayer network," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 28-34.
    • Handle: RePEc:eee:chsofr:v:86:y:2016:i:c:p:28-34
    DOI: 10.1016/j.chaos.2016.01.027
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    Citations

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    Cited by:

    1. Wen, Tao & Jiang, Wen, 2019. "Identifying influential nodes based on fuzzy local dimension in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 332-342.
    2. Wang, Wei & Cai, Kaiquan & Du, Wenbo & Wu, Xin & Tong, Lu (Carol) & Zhu, Xi & Cao, Xianbin, 2020. "Analysis of the Chinese railway system as a complex network," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    3. Zhang, Mingyuan & Liang, Boyuan & Wang, Sheng & Perc, Matjaž & Du, Wenbo & Cao, Xianbin, 2018. "Analysis of flight conflicts in the Chinese air route network," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 97-102.
    4. Yang Yong & Xu Kaijun & Xiang Honghui, 2019. "Analysis on Chinese Airline Network Invulnerability," Journal of Systems Science and Information, De Gruyter, vol. 7(4), pages 359-372, August.
    5. Qian Liu & Wenchen Han & Lixing Lei & Qionglin Dai & Junzhong Yang, 2019. "Chaos Synchronization in Time-Dependent Duplex Networks," Complexity, Hindawi, vol. 2019, pages 1-8, April.
    6. Wang, Yiqiao & Lu, Qiaoyi & Cao, Xianbin & Zhou, Xuesong & Latora, Vito & Tong, Lu Carol & Du, Wenbo, 2020. "Travel time analysis in the Chinese coupled aviation and high-speed rail network," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    7. Zhang, Ronda J. & Ye, Fred Y., 2020. "Measuring similarity for clarifying layer difference in multiplex ad hoc duplex information networks," Journal of Informetrics, Elsevier, vol. 14(1).
    8. Wang, Xinglong & Peng, Jinhan & Tang, Junqing & Lu, Qiuchen & Li, Xiaowei, 2022. "Investigating the impact of adding new airline routes on air transportation resilience in China," Transport Policy, Elsevier, vol. 125(C), pages 79-95.

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