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Academic Journal of Engineering and Technology Science, 2019, 2(3); doi: 10.25236/AJETS.020052.

Topological Properties and Destruction Resistance Analysis of Shenzhen Metro Network

Author(s)

Hailong Wang

Corresponding Author:
Hailong Wang
Affiliation(s)

Department of Transportation College, Shanghai Maritime University, Shanghai, 201306, China
15221934968@163.com

Abstract

In order to analyze the topological properties of complex Metro network, this paper takes Shenzhen as an example, choosing 8 metro lines in Shenzhen as of August 2019 and 168 station nodes as sample data, and constructing a complex network model based on adjacent stations using complex network theory. This method takes metro traffic stations as nodes and metro traffic lines between adjacent stations as edges, which makes the network have the topological properties of complex networks. The characteristics of node degree, average degree, agglomeration coefficient, average shortest path and centrality in the network are analyzed. In addition, the importance of these sites is explored by some important nodes deliberately destroying. By calculating, it is found that the nodes of Shenzhen Metro network occupied a large proportion between 14 and 30, which is 84%. The average node degree of Shenzhen metro network is 29.6, and the average node degree is between 14 and 30. It shows that Shenzhen Metro has serious traffic connectivity. After deleting the important seven nodes, the average node degree decreases by 4, the average shortest path increases by 0.3, and the network diameter or clustering coefficient changes relatively small, showing that these seven nodes play an important role in the transfer trip and can effectively reduce the average transfer times. These laws provide a new reference for optimizing Shenzhen metro traffic network and traffic planning development.

Keywords

Complex network, network connectivity, network optimization, topology characteristics, metro network

Cite This Paper

Hailong Wang. Topological Properties and Destruction Resistance Analysis of Shenzhen Metro Network. Academic Journal of Engineering and Technology Science (2019) Vol. 2 Issue 3: 24-35. https://doi.org/10.25236/AJETS.020052.

References

[1] Liu Zhixiang. Research on robustness of weighted network for urban rail transit. Lanzhou Jiaotong University. 2017.06.
[2] Qu Yingchun, Xu Zhongzhi, Gong Hang, Huang Zhiren and Wang Pu. Vulnerability analysis of urban rail transit network. Journal of Railway Science and Engineering Volume 13, No. 11.2016.11.
[3] Lai Liping. Study on the Complex Characteristics of Urban Rail Transit Network. Journal of Chifeng University (Natural Science Edition), Vol. 33, No. 4 (I). 2017.04.
[4] Li Qian. Importance evaluation of urban rail transit network nodes and cascade failure survivability study. Beijing Jiaotong Universit.2017.03
[5] Jinguang, Masson Flower. Based on complex theory, the network vulnerability of rail transit is analyzed. Agricultural machinery of the times. Volume 44, No. 6.2017.06.
[6] Casey P. Shannon, Virginia Chen, Mandeep Takhar, Zsuzsanna Hollander, Robert Balshaw, Bruce M. McManus, Scott J. Tebbutt, Don D. Sin, Raymond T. Ng. SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations. BMC Bioinformatics,  2016,, Vol.17 (1).2016.12.
[7] Laurie A. Schintler, Rajendra Kulkarni, Sean Gorman, Roger Stough. Using Raster-Based GIS and Graph Theory to Analyze Complex Networks. Networks and Spatial Economics, 2007, Vol.7 (4), pp.301-313. 2007.12.
[8] Kentaro Katahira, Kazuo Okanoya, Masato Okada. A neural network model for generating complex birdsong syntax. Biological Cybernetics,2007,Vol.97 (5-6), pp.441-448.2007.12.
[9] J. Reichardt, D. R. White. Role models for complex networks. The European Physical Journal B,2007,Vol.60 (2), pp.217-224.2007.11.
[10] S. Shabbih. U. H. Jafri, P. Johnson, A. T. Bendiab. Modeling complex network systems architecture and growth. SPIE-the International Society for Optical Engineering. 2007.10.
[11] Glenn Lawyer. Measuring the potential of individual airports for pandemic spread over the world airline network. BMC Infectious Diseases, 2015,Vol.16 (1). 2015.12.
[12] Wu Jianjun. Study on the Complexity of Urban Traffic Network Topology [D]. Beijing Jiaotong University. 2008.