On Two-Dimensional Structural Information Of Beijing Transportation Networks Based On Traffic Big Data

Hierarchy is a fundamental characteristic of many complex systems. The methods of structural information have been taken as a prospective way for quantifying dynamical network complexity. This paper is based on the study of the high-dimensional natural structural information entropy in networks. And then we propose a new similarity District Structural Information (DSI) index, which takes the characteristics of network districts into consideration, to analyze the complexity of dynamical network districts. Based on the method, this paper applies the district structural information to explain the equilibrium problem in real-world networks. And taking Beijing traffic network and its districts to complete experiments demonstrates that the DSI index can reflect the equilibrium of the network and the districts effectively.