Dynamical evolution of complex airline system

Abstract

As a typical open complex system, airline network usually interplays with the economic environment during its self-organized evolution. In this paper, we investigate empirically the correlation between gross domestic product (GDP) and the Chinese airline network (CAN). It is found that the degree of the node has formed a linear correlation with its corresponding GDP since 1998 while a year later the CAN began to exhibit double-power-law degree distribution. Based on the observation, the dynamical equation of CAN is derived. A multiplicative process-like evolution pattern, which strongly depends on the GDP growth rate, is obtained. We demonstrate that such a process coupled with the exponential increase of nodes can yield a double-power-law distribution. The simulation is applied to CAN and we find that the simulation result is in agreement with real CAN.