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Evolution of Chinese Airport Network

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Journal Physica A
Date 2020 Apr 15
PMID 32288080
Citations 10
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Abstract

With the rapid development of the economy and the accelerated globalization process, the aviation industry plays a more and more critical role in today's world, in both developed and developing countries. As the infrastructure of aviation industry, the airport network is one of the most important indicators of economic growth. In this paper, we investigate the evolution of the Chinese airport network (CAN) via complex network theory. It is found that although the topology of CAN has remained steady during the past few years, there are many dynamic switchings inside the network, which have changed the relative importance of airports and airlines. Moreover, we investigate the evolution of traffic flow (passengers and cargoes) on CAN. It is found that the traffic continues to grow in an exponential form and has evident seasonal fluctuations. We also found that cargo traffic and passenger traffic are positively related but the correlations are quite different for different kinds of cities.

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References
1.
Brockmann D, Hufnagel L, Geisel T . The scaling laws of human travel. Nature. 2006; 439(7075):462-5. DOI: 10.1038/nature04292. View

2.
Arenas A, Diaz-Guilera A, Guimera R . Communication in networks with hierarchical branching. Phys Rev Lett. 2001; 86(14):3196-9. DOI: 10.1103/PhysRevLett.86.3196. View

3.
Rong Z, Li X, Wang X . Roles of mixing patterns in cooperation on a scale-free networked game. Phys Rev E Stat Nonlin Soft Matter Phys. 2007; 76(2 Pt 2):027101. DOI: 10.1103/PhysRevE.76.027101. View

4.
Barrat A, Barthelemy M, Pastor-Satorras R, Vespignani A . The architecture of complex weighted networks. Proc Natl Acad Sci U S A. 2004; 101(11):3747-52. PMC: 374315. DOI: 10.1073/pnas.0400087101. View

5.
Barrat A, Barthelemy M, Vespignani A . Weighted evolving networks: coupling topology and weight dynamics. Phys Rev Lett. 2004; 92(22):228701. DOI: 10.1103/PhysRevLett.92.228701. View