奥地利航空公司航班网络拓扑
Network Topology of the Austrian Airline Flights
摘要：
利用复杂网络的概念，对奥地利航空公司的航班信息进行了收集和定量分析。它显示了小世界网络的一些特征，即大的聚类系数和小的平均最短路径长度。网络的度分布揭示了幂律行为，指数值为2 $\sim$ 3的小度分支，但一个平坦的尾巴为大度分支。同样，小重量支线的飞行重量分布也表现出幂律特性。此外，我们发现，该航班网络的聚类系数$C$，0.206，大大大于一个随机网络，其中具有相同的数量的机场（$N$）和平均度（$<k>$）的0.01，和直径$D$，2.383，该航班网络是显着小于相同的随机网络的值，18.67。此外，度-度相关分析表明，网络具有离散行为，即大型机场可能链接到较小的机场。聚类系数分析表明，大型机场呈现出明显的等级组织特征。
英文摘要：
The information of the Austrian airline flights was collected and quantitatively analyzed by the concepts of complex network. It displays some features of small-world networks, namely large clustering coefficient and small average shortest-path length. The degree distributions of the networks reveal power law behavior with exponent value of 2 $\sim$ 3 for the small degree branch but a flat tail for the large degree branch. Similarly, the flight weight distributions show power-law behavior for the small weight branch. Furthermore, we found that the clustering coefficient $C$, 0.206, of this flight network is greatly larger than that of a random network, 0.01, which has the same numbers of the airports ($N$) and mean degree ($<k>$), and the diameter $D$, 2.383, of the flight network is significantly smaller than the value of the same random network, 18.67. In addition, the degree-degree correlation analysis shows the network has disassortative behavior, i.e. the large airports are likely to link to smaller airports. Furthermore, the clustering coefficient analysis indicates that the large airports reveal the hierarchical organization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
