【摘 要】
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We analyse the directed, weighted and evolutionary US flight network, in which vertices are the airports and the flights connecting two airports represent the e
【机 构】
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Institute of Particle Physics, Huashong Normal University, Wuhan 430079“,”Department of Physics, Hua
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We analyse the directed, weighted and evolutionary US flight network, in which vertices are the airports and the flights connecting two airports represent the edges. It is shown that such a network displays two important features recently found in small-world networks. First, the average shortest-path length is 2.4 s, the clustering coefficient of the entire network, 0.618, is greatly larger than that of the random networks with the same N system size)and (average degree), 0.065. We study the detailed flight information both in a week and on a whole.In both the cases, using the Pareto distributions, we find the degree distributions follow two-segment power laws. The weight distributions have power-law tails with the exponents of around 2, and the clustering coefficient distributions follow linear distributions.
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