[1] 武喜萍, 杨红雨, 韩松臣. 基于复杂网络的空中交通特征与延误传播分析[J]. 航空学报, 2017, 38(S1):721473. WU X P, YANG H Y, HAN S C. Analysis of properties and delay propagation of air traffic based on complex network[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(S1):721473(in Chinese). [2] 李善梅. 空中交通拥挤的识别与预测方法研究[D]. 天津:天津大学, 2014:22-35. LI S M. Research on identification and prediction methods of air traffic congestion[D]. Tianjin:Tianjin University, 2014:22-35(in Chinese). [3] PIEN K C, HAN K, SHANG W L, et al. Robustness analysis of the European air traffic network[J].Transportmetrica A:Transport Science, 2015, 11(9):772-792. [4] XU Z W, HARRISS R. Exploring the structure of the US intercity passenger air transportation network:A weighted complex network approach[J].GeoJournal, 2008, 73(2):87-102. [5] 王兴隆, 齐雁楠, 潘维煌. 基于功能脆弱性的空中交通相依网络流量分配[J]. 航空学报, 2020, 41(4):323479. WANG X L, QI Y N, PAN W H. Flow allocation of air traffic interdependent network based on functional vulnerability[J].Acta Aeronautica et Astronautica Sinica, 2020, 41(4):323479(in Chinese). [6] ZHANG J, CAO X B, DU W B, et al.Evolution of Chinese airport network[J]. Physica A:Statistical Mechanics and Its Applications, 2010, 389(18):3922-3931. [7] 陈娱, 王姣娥, 金凤君. 中国国内航空网络的可靠性评价[J]. 地理与地理信息科学, 2015, 31(3):59-64, 2. CHEN Y, WANG J E,JIN F J. Robustness and fragility of Chinese air transport network[J]. Geography and Geo-Information Science, 2015, 31(3):59-64, 2(in Chinese). [8] DINH L T, PASMAN H, GAO X D, et al. Resilience engineering of industrial processes:Principles and contributing factors[J]. Journal of Loss Prevention in the Process Industries, 2012, 25(2):233-241. [9] PRŽULJ N. Biological network comparison using graphlet degree distribution[J]. Bioinformatics, 2007, 23(2):e177-e183. [10] MENCK P J, HEITZIG J, KURTHS J, et al. How dead ends undermine power grid stability[J]. Nature Communications, 2014, 5:3969. [11] 李凡, 张杰勇. 指挥信息系统网络结构的韧性问题研究[J]. 电光与控制, 2020, 27(4):49-54. LI F, ZHANG J Y. On resilience of network structure of command information system[J]. Electronics Optics & Control, 2020, 27(4):49-54(in Chinese). [12] TANG J Q, HEINIMANN H, HAN K, et al. Evaluating resilience in urban transportation systems for sustainability:A systems-based Bayesian network model[J]. Transportation Research Part C:Emerging Technologies, 2020, 121:102840. [13] SHEN-ORR SS, MILO R, MANGAN S, et al. Network motifs in the transcriptional regulation network of Escherichia coli[J]. Nature Genetics, 2002, 31(1):64-68. [14] SCHULTZ P, HEITZIG J, KURTHS J. Detours around basin stability in power networks[J]. New Journal of Physics, 2014, 16(12):125001. [15] GOROCHOWSKI T E, GRIERSON C S, DI BERNARDO M. Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks[J]. Science Advances, 2018, 4(3):eaap9751. [16] LESKOVEC J, HORVITZ E. Planetary-scale views on an instant-messaging network[DB/OL]. arxiv preprint:0803.0939,2008. [17] 丁明, 韩平平. 加权拓扑模型下的小世界电网脆弱性评估[J]. 中国电机工程学报, 2008, 28(10):20-25. DING M, HAN PP. Vulnerability assessment to small-world power grid based on weighted topological model[J]. Proceedings of the CSEE, 2008, 28(10):20-25(in Chinese). [18] CHASSIN D P, POSSE C. Evaluating North American electric grid reliability using the Barabási-Albert network model[J]. Physica A:Statistical Mechanics and Its Applications, 2005, 355(2-4):667-677. [19] 徐立新. 基于复杂系统理论的电网故障时空分布特性及结构脆弱性研究[D]. 广州:华南理工大学, 2014:90-99. XU L X. Study on fault's temporal-spatial distribution characteristics and structural vulnerability in power grid based on complex system theory[D]. Guangzhou:South China University of Technology, 2014:90-99(in Chinese). [20] 刘咏梅, 彭琳, 赵振军. 基于小世界网络的微博谣言传播演进研究[J]. 复杂系统与复杂性科学, 2014, 11(4):54-60. LIU Y M, PENG L, ZHAO Z J. The evolution of rumor spread onmicrblog based on small-world network[J]. Complex Systems and Complexity Science, 2014, 11(4):54-60(in Chinese). [21] KURANT M, THIRAN P. Extraction and analysis of traffic and topologies of transportation networks[J]. Physical Review E, Statistical, Nonlinear, and Soft Matter Physics, 2006, 74(3pt 2):036114. [22] WERNICKE S, RASCHE F. FANMOD:A tool for fast network motif detection[J]. Bioinformatics, 2006, 22(9):1152-1153. [23] WERNICKE S. Efficient detection of network motifs[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2006, 3(4):347-359. [24] OSEI-ASAMOAH A, LOWNES N E. Complex network method of evaluating resilience in surface transportation networks[J]. Transportation Research Record:Journal of the Transportation Research Board, 2014, 2467(1):120-128. [25] WANG Y J, ZHAN J M, XU X H, et al. Measuring the resilience of an airport network[J]. Chinese Journal of Aeronautics, 2019, 32(12):2694-2705. [26] 李兆隆, 金淳, 胡畔, 等. 基于弹复性的交通网络应急恢复阶段策略优化[J]. 系统工程理论与实践, 2019, 39(11):2828-2841. LI Z L, JIN C, HU P, et al.Resilience-based recovery strategy optimization in emergency recovery phase for transportation networks[J]. Systems Engineering-Theory & Practice, 2019, 39(11):2828-2841(in Chinese). [27] 缪莉莉, 韩传峰, 刘亮, 等. 基于模体的科学家合作网络基元特征分析[J]. 科学学研究, 2012, 30(10):1468-1475. MIAO L L, HAN C F, LIU L, et al. Using motif to characterize building block of scientific collaboration networks[J]. Studies in Science of Science, 2012, 30(10):1468-1475(in Chinese). |