Exploring evolutionary features of directed weighted hazard network in the subway construction

doi:10.1088/1674-1056/28/3/038901

Abstract

A better understanding of previous accidents is an effective way to reduce the occurrence of similar accidents in the future. In this paper, a complex network approach is adopted to construct a directed weighted hazard network (DWHN) to analyze topological features and evolution of accidents in the subway construction. The nodes are hazards and accidents, the edges are multiple relationships of these nodes and the weight of edges are occurrence times of repetitive relationships. The results indicate that the DWHN possesses the property of small-world with small average path length and large clustering coefficient, indicating that hazards have better connectivity and will spread widely and quickly in the network. Moreover, the DWHN has the property of scale-free network for the cumulative degree distribution follows a power-law distribution. It makes DWHN more vulnerable to target attacks. Controlling key nodes with higher degree, strength and betweenness centrality will destroy the connectivity of DWHN and mitigate the spreading of accidents in the network. This study is helpful for discovering inner relationships and evolutionary features of hazards and accidents in the subway construction.

Keywords: accident analysis directed weighted network complex network evolutionary features

Received: 08 December 2018
Revised: 01 January 2019
Accepted manuscript online:

PACS:	89.75.Fb	(Structures and organization in complex systems)
	89.40.-a	(Transportation)
	89.20.Kk	(Engineering)

Fund:

Project supported by the Co-Funding of National Natural Science Foundation of China and Shenhua Group Corporation Ltd (Grant No. U1261212) and the Program of Major Achievements Transformation and Industrialization of Beijing Education Commission, China (Grant No. ZDZH20141141301).

Corresponding Authors: Cong Jin
E-mail: tbp1600602049@student.cumtb.edu.cn

Cite this article:

Gong-Yu Hou(侯公羽), Cong Jin(靳聪), Zhe-Dong Xu(许哲东), Ping Yu(于萍), Yi-Yi Cao(曹怡怡) Exploring evolutionary features of directed weighted hazard network in the subway construction 2019 Chin. Phys. B 28 038901

[1]	Younes M B and Boukerche A 2015 Ad. Hoc. Netw. 24 317
[2]	Kong X J, Xu Z Z, Shen G J, Wang J Z, Yang Q Y and Zhang B S 2016 Future Gener. Comp. Sy. 61 97
[3]	Li Q M, Song L L, List G F, Deng Y L, Zhou Z P and Liu P 2017 Saf. Sci. 93 50
[4]	Zhang X L, Deng Y L, Li Q M, Skitmore M and Zhou Z P 2016 Saf. Sci. 84 88
[5]	Ding L Y, Yu H L, Li H, Zhou C, Wu X G and Yu M H 2012 Automat. Constr. 27 120
[6]	Ding L Y, Zhang L M, Wu X G, Skibniewski M J and Yu Q Z 2014 Saf. Sci. 62 8
[7]	Hangzhou Government 2010 1994 Interfaces 24 19
[8]	Saaty T L 1994 Interfaces 24 19
[9]	Vaidyaab O S 2006 Eur. J. Oper. Res. 169 1
[10]	Li X P and Li Y N 2014 Tunn. Undergr. Sp. Tech. 40 182
[11]	Tseng C H, Cheng S T, Wang Y H and Peng J T 2008 Phys. A 387 3192
[12]	Hou G Y, Liang R, Sun L, Liu L and Gong Y F 2014 Acta Phys. Sin. 63 090505 (in Chinese)
[13]	Boubou R, Emeriault F and Kastner R 2010 Can. Geotech. J. 47 1214
[14]	Zhang Y and Wang X Y 2012 Chin. Phys. B 21 020507
[15]	Jiang A N, Wang S Y and Tang S L 2011 Automat. Constr. 20 482
[16]	Widodo A and Yang B S 2007 Mech. Syst. Signal Pr. 21 2560
[17]	Salmon P M, Cornelissen M and Trotter M J 2012 Saf. Sci. 50 1158
[18]	Branford K 2011 Aviation Psychol. Appl. Hum. Factors 1 31
[19]	Salmon P M, Goode N, Archer F, Spencer C, Mcardle D and Mcclure R J 2014 Saf. Sci. 70 114
[20]	Ouyang M, Hong L, Yu M H and Fei Q 2010 Saf. Sci. 48 544
[21]	Eleye-Datubo A G, Wall A and Wang J 2008 Risk Anal. 28 95
[22]	Zhang L M, Wu X G, Qin Y W, Skibniewski M J and Liu W L 2016 Risk Anal. 36 278
[23]	Diller T, Helmrich G, Dunning S, Cox S, Buchanan A and Shappell S 2014 Am. J. Med. Qual. 29 181
[24]	Shi L, Shuai J and Xu K 2014 J. Hazard. Mater. 278 529
[25]	Lavasani S M, Zendegani A and Celik M 2015 Process Saf. Environ. 93 75
[26]	Zhou T, Bai W J, Wang B H, Liu Z J and Yang G 2005 Physics 34 31 (in Chinese)
[27]	Yao H, Zhang J W and Di Z R 2010 Physics 39 190 (in Chinese)
[28]	Alexei V, Romualdo P S and Alessandro V 2002 Phys. Rev. E 65 066130
[29]	Bawden D 2004 Evolution and Structure of the Internet: A Statistical Physics Approach (Cambridge: Cambridge Univeristy Press) pp. 449-452
[30]	Wagner A 2001 Mol. Biol. Evol. 18 1283
[31]	Romualdo P S, Eric S and Solé R V 2003 J. Theor. Biol. 222 199
[32]	Zheng Z G and Qian Y 2018 Chin. Phys. B 27 018901
[33]	Latora V and Marchiori M 2002 Physica A 314 109
[34]	Cai K Q, Zhang J, Du W B and Cao X B 2012 Chin. Phys. B 21 028903
[35]	Jiang J, Zhang R, Guo L, Li W and Cai X 2016 Chin. Phys. Lett. 33 108901
[36]	Niu R W and Pan G J 2016 Chin. Phys. Lett. 33 068901
[37]	Xing X, Yu D X, Tian X J and Wang S G 2017 Acta Phys. Sin. 66 230501 (in Chinese)
[38]	Albert R, Jeong H and Barabási A L 1999 Nature 401 130
[39]	Barabási A L, Albert R and Jeong H 2000 Physica A 281 69
[40]	Li H J, An H Z, Huang J C, Gao X Y and Shi Y L 2014 Acta Phys. Sin. 63 048901 (in Chinese)
[41]	Liao H, Shen J, Wu X T, Chen B K and Zhou M Y 2017 Chin. Phys. B 26 110505
[42]	Gao X Y, An H Z and Fang W 2012 Acta Phys. Sin. 61 098902 (in Chinese)
[43]	Gao X Y, An H Z, Liu H H and Ding Y H 2011 Acta Phys. Sin. 60 068902 (in Chinese)
[44]	Luo Z Y, Li K P, Ma X and Zhou J 2014 Proceedings of the 2013 International Conference on Electrical and Information Technologies for Rail Transportation, November 7-10, 2013 Changchun, China, p. 513
[45]	Zhou Z P and Irizarry J 2016 J. Manage. Eng. 32 05016013
[46]	Zhou Z P, Irizarry J and Li Q M 2014 Saf. Sci. 64 127
[47]	Gao Z K and Jin N D 2012 Nonlinear Anal. 13 947
[48]	Zeng X, Chen J P, Shao J L and Bie L D 2012 Acta Phys. Sin. 61 190510 (in Chinese)
[49]	Zeng M, Wang E H, Zhao M Y and Meng Q H 2017 Acta Phys. Sin. 66 210502 (in Chinese)
[50]	Barthélemy M, Barrat A, Pastor-Satorras R and Vespignani A 2005 Physica A 346 34

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Exploring evolutionary features of directed weighted hazard network in the subway construction

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