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Empirical analysis of airport network and critical airports

Chinese Journal of Aeronautics 2016年第2期29卷 512-519页

作者： Cong Wei Hu Minghua Dong Bin Wang Yanjun Feng Cheng College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing 211106 China National Key Laboratory of Air Traffic Flow Management Nanjing 211106 China The 28th Research Institute of China Electronics Technology Group Corporation Nanjing 210000 China

Air transport network, or airport network, is a complex network involving numerous airports. Effective management of the air transport system requires an in-depth understanding of the roles of airports in the network. Whereas knowledge on air transport network properties has been improved greatly, methods to find critical airports in the network are still lacking. In this paper, we present methods to investigate network properties and to identify critical airports in the network. A novel network model is proposed with airports as nodes and the correlations between traffic flow of airports as edges. Spectral clustering algorithm is developed to classify air- ports. Spatial distribution characteristics and intraclass correlation of different categories of air- ports are carefully analyzed. The analyses based on the fluctuation trend of distance-correlation and power spectrum of time series are performed to examine the self-organized criticality of the net- work. The results indicate that there is one category of airports which dominates the self-organized critical state of the network. Six airports in this category are found to be the most important ones in the Chinese air transport network. The flights delay occurred in these six airports can propagate to the other airports, having huge impact on the operation characteristics of the entire network. The methods proposed here taking traffic dynamics into account are capable of identifying critical air- ports in the whole air transport network.

关键词： airport network Critical airport Spatial correlation Spectral clustering Power-law distributionPower spectra

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Robustness analysis metrics for worldwide airport network：A comprehensive study

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Chinese Journal of Aeronautics 2017年第2期30卷 500-512页

作者： Sun Xiaoqian Volker Gollnick Sebastian Wandelt School of Electronic and Information Engineering Beihang University 100083 Beijing China Beijing Key Laboratory for network-based Cooperative A TM Beijing 100083 China Beijing Laboratory for General Aviation Technology Beijing 100083 China Institute of Air Transportation Systems German Aerospace Center Blohmstrasse 18 21079 Hamburg Germany

Robustness of transportation networks is one of the major challenges of the 21 st *** paper investigates the resilience of global air transportation from a complex network point of view,with focus on attacking strategies in the airport network,i.e.,to remove airports from the system and see what could affect the air traffic system from a passenger＇s ***,we identify commonalities and differences between several robustness measures and attacking strategies,proposing a novel notion of functional robustness：unaffected passengers with *** apply twelve attacking strategies to the worldwide airport network with three weights,and evaluate three robustness *** find that degree and Bonacich based attacks harm passenger weighted network *** evaluation is geared toward a unified view on air transportation network attack and serves as a foundation on how to develop effective mitigation strategies.

关键词： Air transportation systems resilience airport network Attacking strategy Robustness measure

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Vulnerability analysis for airport networks based on fuzzy soft sets: From the structural and functional perspective

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Chinese Journal of Aeronautics 2015年第3期28卷 780-788页

作者： Li Shanmei Xu Xiaohao Air Traffic Management Research Base Civil Aviation University of China

Abstract Recently, much attention has been paid to the reliability and vulnerability of critical infrastructure. In air traffic systems, the vulnerability analysis for airport networks can be used to guide air traffic administrations in their prioritization of the maintenance and repair of airports, as well as to avoid unnecessary disturbances in the planning of flight schedules. In this paper, the evaluation methods of airport importance and network efficiency arc established. Firstly, the evaluation indices of airport importance are proposed from both the topological and functional perspectives. The topological characteristics come from the structure of airport network and the functional features stem from the traffic flow distribution taking place inside the network. Secondly, an integrated evaluation method based on fuzzy soft set theory is proposed to identify the key airports, which can fuse together importance indices over different time intervals. Thirdly, an airport network efficiency method is established for the purpose of assessing the accuracy of the evaluation method. Finally, empirical studies using real traffic data of US and China＇s airport networks show that the evaluation method proposed in this papcr is the most accuratc. Thc vulucrability of US and China＇s airport networks is compared. The similarities and differences between airport geography distribution and airport importance distribution are discussed here and the dynamics of airport importance is studied as well.

关键词： Air traffic airport network Complex networkFuzzy soft sets Key node

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Dynamics of air transport networks：A review from a complex systems perspective

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Chinese Journal of Aeronautics 2017年第2期30卷 469-478页

作者： Luis E.C.Rocha Department of Public Health Sciences Karolinska Institutet Stockholm 17177 Sweden Department of Mathematics University of Namur 5000 Belgium

Air transport systems are highly dynamic at temporal scales from minutes to *** dynamic behavior not only characterizes the evolution of the system but also affect the system＇s *** the evolutionary mechanisms is thus fundamental in order to better design optimal air transport networks that benefits companies,passengers and the *** this review,we briefly present and discuss the state-of-the-art on time-evolving air transport *** distinguish the structural analysis of sequences of network snapshots,ideal for long-term network evolution（*** evolution）,and temporal paths,preferred for short-term dynamics（*** evolution）.We emphasize that most previous research focused on the first modeling approach（***-term） whereas only a few studies look at high-resolution temporal *** conclude the review highlighting that much research remains to be done,both to apply already available methods and to develop new measures for temporal paths on air transport *** particular,we identify that the study of delays,network resilience and optimization of resources（aircraft and crew） are critical topics.

关键词： Air transport airport network Complex network Dynamic network Temporal network

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Analysis of Air Traffic network of China

Analysis of Air Traffic Network of China

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第24届中国控制与决策会议

作者： Hongyong Wang 1 , Ruiying Wen 2 1. Air Traffic Management College, Civil Aviation University of China, Tianjin, 300300, China2. Air Traffic Management College, Civil Aviation University of China, Tianjin, 300300, China

The China Air Traffic System （ATS） is facing several substantial challenges, such as the growth of delay, delay progation and airspace congestion with increasing air traffic flow. As ATS is a complex adaptive system, it is required a systematic analysis. Modern network theory can provide a useful systematic analysis approach to get the mechism from topology structure characteristics. This paper examines two network structures of the current ATS with complex network approach: the airport network of China （ANC） and the Air Route network of China （ARNC）. Measures for overall network structure include degree distribution, average path length and clustering coefficient. Results indicate that the ANC is a small-world （SW） network with short average path length （5.05） and high degree of clustering （0.7659） and its degree distribution follows a double scaling law. Whereas the ARNC just displays scale-free proterty and it isn’t a small-world network with an average path length of 18.1 and a small clustering coefficient of 0.0809.

关键词： airport network air route network air traffic network complex network china

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