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复杂系统与复杂性科学  2019, Vol. 16 Issue (2): 19-30    DOI: 10.13306/j.1672-3813.2019.02.003
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基于复杂网络的两栖水上飞机起降安全风险演化
肖琴, 罗帆
武汉理工大学管理学院,武汉,430070
Safety Risk Evolution of Amphibious Seaplane During Takeoff and Landing ——Based on Complex Network
XIAO Qin, LUO Fan
School of Management, Wuhan University of Technology, Wuhan 430070, China
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摘要 为了揭示两栖水上飞机起降安全风险的演化规律,有效预防水上飞机起降安全风险,以风险因素间的作用路径为基础,构建两栖水上飞机起降安全风险演化的有权有向网络拓扑结构,验证了该复杂网络的无标度特性;采用Matlab编程仿真分析网络在随机攻击和蓄意攻击情况下的功能鲁棒性和结构鲁棒性;对比度值攻击、介数值攻击、接近度中心性值攻击及综合值攻击下的网络鲁棒性效果,识别网络的关键风险因素,提出断链控制策略。研究结果表明:两栖水上飞机起降安全风险网络是无标度网络;该网络对随机攻击具有较强鲁棒性,对蓄意攻击具有脆弱性,且度值攻击的结构鲁棒性最差,综合值攻击的性能鲁棒性最差;综合值较高的节点是网络的关键风险因素,优先处置关键节点有助于预防起降事故
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肖琴
罗帆
关键词 两栖水上飞机起降安全风险演化复杂网络鲁棒性断链控制    
Abstract:In order to reveal the evolution mechanism of the taking off and landing safety risk of amphibious seaplane, and effectively prevent the safety risk of seaplane in taking off and landing stage, the right-oriented network topology structure of the amphibious seaplane take-off and landing safety risk evolution was constructed based on the action path between risk factors, and regression analysis was used to verify the scale-free characteristics of the complex network. The node degree centrality, betweenness centrality, closeness centrality and comprehensive value were applied to identify the key risk factors from different perspectives. Matlab was used to analyze the functional robustness and structural robustness of the network under random and deliberate attacks. The robustness effects of degree attack, betweenness centrality attack, closeness centrality attack, comprehensive attack were contrasted, the key risk factors were identified and the chain-breaking control strategy was proposed. The results show that the safety risk network of amphibious seaplane take-off and landing is a scale-free network; the robustness of the network under random attack is stronger than deliberate attack, and the structural robustness of the degree attack is the worst, and the performance robustness of the comprehensive value attack is the worst; nodes with higher comprehensive values are the key risk factors of the network, and priority disposal of key nodes can help prevent taking off and landing accidents.
Key wordsamphibious seaplane    taking off and landing safety    risk evolution    complex network    robustness    link deletion
收稿日期: 2019-04-29      出版日期: 2019-08-19
ZTFLH:  X949  
基金资助:国家自然科学基金(71271163),教育部人文社科基金(18YJA630076)
通讯作者: 罗帆(1963),女,湖南益阳人,博士,教授,主要研究方向为航空安全,风险预警   
作者简介: 肖琴(1990),女,湖北孝感人,博士研究生,主要研究方向为安全风险管理
引用本文:   
肖琴, 罗帆. 基于复杂网络的两栖水上飞机起降安全风险演化[J]. 复杂系统与复杂性科学, 2019, 16(2): 19-30.
XIAO Qin, LUO Fan. Safety Risk Evolution of Amphibious Seaplane During Takeoff and Landing ——Based on Complex Network. Complex Systems and Complexity Science, 2019, 16(2): 19-30.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2019.02.003      或      http://fzkx.qdu.edu.cn/CN/Y2019/V16/I2/19
[1] 翁建军, 周阳. 水上飞机与船舶碰撞风险因素建模[J]. 中国航海, 2013, 36(3):70-75.Wang Jianjun, Zhou Yang. Analysis of risk factors of seaplane-vessel collision based on the integration of Dematel and ISM[J]. Navigation of China, 2013, 36(3):70-75.
[2] 翁建军, 周阳. 水上飞机与船舶的港口异质交通流建模[J]. 中国航海, 2015, 38(2):104-108.Weng Jianjun, Zhou Yang. Simulation modeling of seaplane-ship heterogeneous port traffic flow[J]. Navigation of China, 2015, 38(2):104-108.
[3] Guo G, Xu Y, Wu B. Overview of current progress and development of seaplane safety management[C]// IEEE International Conference on Intelligent Transportation Engineering, Singapore: IEEE, 2016: 58-63.
[4] 张攀科,罗帆.水上机场航道冲突风险机制的FTA-BN建模[J].中国安全科学学报,2018,28(9):177-182.Zhang Panke, Luo Fan. FTA-BN modeling of runway conflict risk mechanism at water aerodrome [J]. China Safety Science Journal, 2018,28(9):177-182.
[5] 肖琴, 罗帆. 基于GT-SEM的两栖水上飞机起降安全风险作用机理[J]. 中国安全科学学报, 2017, 29(4):159-164.Xiao Qin, Luo Fan. GT-SEM model for safety risk mechanism of amphibious seaplane during taking off and landing[J]. China Safety Science Journal, 2017, 29(4):159-164.
[6] Watts D J, Strogatz S H. Collective dynamics of 'small-world' networks.[J]. Nature, 1998, 393: 440-442.
[7] 刘宏鲲, 周涛. 航空网络研究综述[J]. 自然科学进展, 2008, 18(6):601-608.Liu Hongkun, Zhou Tao. Reviews of aviation network research[J]. Advances in Natural Science, 2008, 18(6):601-608.
[8] Faloutsos M, Faloutsos P, Faloutsos C. On power-law relationships of the Internet topology[J]. Acm Sigcomm Computer Communication Review, 1997, 29(4):251-262.
[9] Hofman J M, Sharma A, Watts D J. Prediction and explanation in social systems.[J]. Science, 2017, 355: 486-488.
[10] Ebel H, Mielsch L I, Bornholdt S. Scale-free topology of e-mail networks[J]. Phys Rev E Stat Nonlin Soft Matter Phys, 2002, 66:035103.
[11] 吴文祥, 黄海军. 固定需求交通网络的一般系统最优模型与性质[J]. 管理科学学报, 2015, 18(12):58-67.Wu Wenxiang, Huang Haijun. Generalized system optimal model and properties in traffic networks with fixed demand[J]. Journal of Management Science in China, 2015, 18(12):58-67.
[12] Wang H, Gu T, Jin M, et al. The complexity measurement and evolution analysis of supply chain network under disruption risks[J]. Chaos, Solitons & Fractals, 2018, 116:72-78.
[13] Wen X, Tu C, Wu M. Node importance evaluation in aviation network based on “no return” node deletion method[J]. Physica A: Statistical Mechanics and its Applications, 2018, 503: 546-559.
[14] Lordan O, Sallan J M, Simo P. Study of the topology and robustness of airline route networks from the complex network approach: a survey and research agenda[J]. Journal of Transport Geography, 2014, 37:112-120.
[15] Lordan O, Sallan J M, Simo P, et al. Robustness of airline alliance route networks[J]. Communications in Nonlinear Science and Numerical Simulation, 2015, 22(1-3):587-595.
[16] Lordan O, Sallan J M, Escorihuela N, et al. Robustness of airline route networks[J]. Physica A: Statistical Mechanics and its Applications, 2016, 445:18-26.
[17] Zhou Y M, Wang J W, Huang G Q. Efficiency and robustness of weighted air transport networks [J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 122: 14- 26.
[18] Voltes-Dorta A, Rodríguez-Déniz H, Suau-Sanchez P. Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays: Ranking the most critical airports[J]. Transportation Research Part A: Policy and Practice, 2017, 96:119-145.
[19] Hossain M M, Alam S. A complex network approach towards modeling and analysis of the Australian Airport Network[J]. Journal of Air Transport Management, 2017, 60:1-9.
[20] Cong W, Hu M, Dong B, et al. Empirical analysis of airport network and critical airports[J]. Chinese Journal of Aeronautics, 2016, 29(2):512-519.
[21] Dai L, Derudder B, Liu X. The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979-2012[J]. Journal of Transport Geography, 2018, 68:67-77.
[22] Wang H, Song Z, Wen R, et al. Study on evolution characteristics of air traffic situation complexity based on complex network theory[J]. Aerospace Science and Technology, 2016, 58:518-528.
[23] Jimenez E, Claro J, Jorge P D S. Spatial and commercial evolution of aviation networks: a case study in mainland Portugal[J]. Journal of Transport Geography, 2012, 24:383-395.
[24] 赵贤利, 罗帆. 基于复杂网络理论的机场飞行区风险演化模型研究[J]. 电子科技大学学报(社会科学版), 2013, 15(4):31-34.Zhao Xianli, Luo Fan. Research on the risks evolution model based on complex networks in airport flight area[J]. Journal of UESTC(Social Science Edition), 2013, 15(4):31-34.
[25] Guimerá, R., Amaral L A N. Modeling the world-wide airport network[J]. The European Physical Journal B-Condensed Matter and Complex Systems, 2004, 38(2):381-385.
[26] Guimerà, R., Mossa, A. Turtschi, et al. The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(22):7794-7799.
[27] 刘宏鲲, 周涛. 中国城市航空网络的实证研究与分析[J]. 物理学报, 2007, 56(1):106-112.Liu Hongkun, Zhou Tao. Empirical study of Chinese city airline network [J]. Acta Physica Sinica, 2007, 56(1):106-112.
[28] Erdös P, Rényi A. On the evolution of random graphs[J]. Publication of the Mathematical Institute of the Hungarian Academy of Science, 1960, 5:17-60.
[29] Milgram S. The small world problem[J]. Psychology Today. 1967, 2:60-67.
[30] Newman M E J, Watts D J. Renormalization group analysis of the small-world network model [J]. Physics Letters A, 1999, 263:341-346.
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