Please wait a minute...
文章检索
复杂系统与复杂性科学  2015, Vol. 12 Issue (1): 40-45    DOI: 10.13306/j.1672-3813.2015.01.006
  本期目录 | 过刊浏览 | 高级检索 |
基于复杂网络的空铁复合网络的鲁棒性研究
徐凤1,2, 朱金福1, 苗建军1
1.南京航空航天大学,南京 210016;
2.南京交通职业技术学院,南京 211188
The Robustness of High-Speed Railway and Civil Aviation Compound Network Based on the Complex Network Theory
XU Feng1,2, ZHU Jinfu1, MIAO Jianjun1
1. Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
2. Nanjing Communications Institute of Technology, Nanjing 211188, China
全文: PDF(904 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 运用复杂网络方法,对中国高铁-民航复合网络进行了网络拓扑特性与鲁棒性分析。分析结果表明,高铁-民航复合网络及其子网络都是具有无标度特性的小世界网络;高铁-民航复合网络在蓄意攻击模式下的鲁棒性较差,而在随机性攻击模式下的鲁棒性较强;无论是随机性攻击还是蓄意攻击,复合网络的鲁棒性都优于高铁子网络和航空子网络。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
徐凤
朱金福
苗建军
关键词 高速铁路民航复杂网络鲁棒性    
Abstract:The topological characteristics and robustness of Chinese high-speed railway and civil aviation compound network are analyzed based on the complex network theory. The results include the following points: the high-speed railway and civil aviation compound network and its two subnetworks are scale-free and small-world networks; the robustness of high-speed railway and civil aviation compound network is better under the random attack than under the calculated attack; the robustness of compound network is better than its two subnetworks,whether under the random attack or under the calculated attack.
Key wordshigh-speed railway    civil aviation    complex networks    robustness
收稿日期: 2013-12-03      出版日期: 2026-06-22
ZTFLH:  U113  
基金资助:中央高校基本科研业务费专项资金:江苏省研究生培养创新工程(KYLX_0293);国家自然科学基金(71171111);中国民用航空局专项基金(KFA1152401)
作者简介: 徐凤(1981-),女,江苏徐州人,博士研究生,讲师,主要研究方向为交通运输规划与管理。
引用本文:   
徐凤, 朱金福, 苗建军. 基于复杂网络的空铁复合网络的鲁棒性研究[J]. 复杂系统与复杂性科学, 2015, 12(1): 40-45.
XU Feng, ZHU Jinfu, MIAO Jianjun. The Robustness of High-Speed Railway and Civil Aviation Compound Network Based on the Complex Network Theory[J]. Complex Systems and Complexity Science, 2015, 12(1): 40-45.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2015.01.006      或      https://fzkx.qdu.edu.cn/CN/Y2015/V12/I1/40
[1] Sen P, Dasgupta S, Chatterjee A, et al. Small-world properties of the Indian railway network[J]. Phys Rev E, 2003, 67(3): 036106.
[2] Kurant M, Thiran P. Extraction and analysis of traffic and topologies of transportation networks[J]. Phys Rev E, 2006, 74(3):036114.
[3] Bagler G. Analysis of the airport network of India as a complex weighted network[J]. Physica, 2008, 387: 2972-2980.
[4] Michele G, Funaro M. Topology of the Italian airport network: a scale-free small-world network with a fractal structure?[J]. Chaos, Solitons and Fractals, 2007, 31: 527-536.
[5] 赵伟,何红生,林中材,等.中国铁路客运网网络性质的研究[J].物理学报,2006, 55(8):3906-3911.
Zhao Wei, He Hongsheng, Lin Zhongcai, et al. The study of properties of Chinese railway passenger transport network[J]. Acta Physica Sinica, 2006, 55(8):3906-3911.
[6] 唐芙蓉,杨先清,唐刚,等.中国铁路交通网络的拓扑研究及客流分析[J].中国矿业大学学报,2010,39(6):935-940.
Tang Furong, Yang Xianqing, Tang Gang, et al. Study of the topology of Chinese rail network and its passengers flow[J]. Journal of China University of Mining &Technology, 2010, 39(6):935-940.
[7] Li W, Cai X. Statistical analysis of airport network of China[J]. Phys Rev E, 2004, 69(4): 046106.
[8] 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 civil aviation network[J]. Acta Physica Sinica, 2007, 56(1): 106-112.
[9] Albert R, Jeong H, Barabasi A L. Attack and error tolerance of complex networks[J]. Nature.2000, 406: 378-382.
[10] Holme P, Kim B J. Attack vulnerability of complex networks[J]. Phys Rev E, 2002, 65(6):066109.
[11] 江永超.基于复杂网络理论的铁路网可靠性分析[D].成都:西南交通大学,2011.
Jiang Yongchao. Study on reliability of railway network based on complex network theory[D]. Chengdu: Southwest Jiaotong University, 2011.
[12] 姜涛,朱金福,覃义.基于最短路的中枢辐射航线网络鲁棒优化方法[J].系统工程,2007, 25(1): 53-59.
Jiang Tao, Zhu Jinfu, Tan Yi. Robust optimization of hub-and-spoke civil aviation network design based on shortest path algorithm[J]. Systems Engineering, 2007, 25(1): 53-59.
[13] 柏明国,姜涛,朱金福.基于禁忌算法的中枢辐射航线网络鲁棒优化方法[J].数学的实践与认识,2008, 38(13): 60-69.
Bai Mingguo, Jiang Tao, Zhu Jinfu.The robust optimization of the hub and spoke civil aviation network design based on Tabu search[J]. Mathematics in Practice and Theory, 2008, 38(13): 60-69.
[14] 徐凤,朱金福,杨文东.高铁-民航复合网络的构建及网络拓扑特性分析[J].复杂系统与复杂性科学,2013,10(3):1-11.
Xu Feng, Zhu Jinfu, Yang Wendong. Construction of high-speed railway and airline compound network and the analysis of its network topology characteristics[J]. Complex Systems and Complexity Science, 2013, 10(3):1-11.
[1] 岳芳, 张涵, 樊茂瑞, 戴文慧, 郭剑锋. 开放式交互平台知识协同中的群体观点演化模型与实证[J]. 复杂系统与复杂性科学, 2026, 23(2): 8-18.
[2] 韩继辉, 张程义, 石月凤, 胡颖. 层节点攻击模式下的多层网络最优拆解算法[J]. 复杂系统与复杂性科学, 2026, 23(2): 19-25.
[3] 孙艳琴, 吴怀宇, 陈志环. 异维异构多重边复杂网络的广义外同步控制[J]. 复杂系统与复杂性科学, 2026, 23(2): 34-40.
[4] 高彦丽, 陈光明, 陈世明. 基于负载重分配的边相依加权网络鲁棒性研究[J]. 复杂系统与复杂性科学, 2026, 23(2): 41-47.
[5] 于海波, 高彦丽, 陈世明, 凤超. 异质耦合下铁路-经济多层网络鲁棒性分析[J]. 复杂系统与复杂性科学, 2026, 23(2): 48-56.
[6] 聂廷远, 王艳伟, 聂晶晶, 刘鹏飞. 基于注意力机制和复杂网络的FPGA可布性预测[J]. 复杂系统与复杂性科学, 2026, 23(1): 53-59.
[7] 户佐安, 杨江浩, 邓锦程. 考虑多元变量的世界航空网络综合鲁棒性研究[J]. 复杂系统与复杂性科学, 2026, 23(1): 60-69.
[8] 潘文祥, 李东艳, 孙思翔, 佟宁. 一种基于社团外围节点的网络鲁棒性优化策略[J]. 复杂系统与复杂性科学, 2026, 23(1): 70-78.
[9] 胡金梅, 邹艳丽, 王鸿俊, 张海. 基于二阶邻居负载再分配的电网级联故障研究[J]. 复杂系统与复杂性科学, 2026, 23(1): 1-9.
[10] 孙小慧, 刘毅, 米玉梅, 吕凯. 韧性视角下城市地铁与常规公交网络关键站点及线路识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 26-36.
[11] 牟奇锋, 李晓倩. 基于邻接矩阵的复杂网络演化融合迭代方法[J]. 复杂系统与复杂性科学, 2026, 23(1): 79-86.
[12] 孙文静, 余路粉, 潘文林, 蓝春江. 基于节点影响因子和贡献因子的复杂网络重要节点识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 87-95.
[13] 卢新彪, 刘泽诚, 陈贵允, 杨铁流, 高兴. 基于图卷积网络的复杂网络能控性提升方法[J]. 复杂系统与复杂性科学, 2025, 22(4): 24-28.
[14] 周青, 李依函, 陈文冲. “互联网+”企业创新生态系统网络演化分析[J]. 复杂系统与复杂性科学, 2025, 22(4): 1-7.
[15] 余文倩, 马福祥, 陈阳, 马秀娟. 基于自适应的高阶网络鲁棒性分析[J]. 复杂系统与复杂性科学, 2025, 22(4): 15-23.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed