Research on evolution of air traffic flow fluctuations based on integration


	encoding transition network

Abstract

Abstract:

In order to break through the limitations of previous research that only focused on the direction of air traffic flow

fluctuations, and to fully highlight the actual operational information such as flow fluctuation status and airport capacity limitations in the study of air traffic flow dynamic evolution, a fusion encoding transition network construction method is proposed using dynamic coarse-grained encoding method to symbolically encode the airport flow

volume ratio and flow fluctuation gradient and merge into fluctuation modal. Quantitative analysis and qualitative

identification study are conducted on the evolution laws and characteristics of air traffic flow fluctuations from a

complex network perspective, focusing on the 24-hour and coordinated time periods of Beijing Daxing International Airport (Daxing Airport). The research results indicate that the differences in the evolution of air traffic flow

fluctuations between the two periods at Daxing Airport are mainly concentrated at the macro level. The evolution of

flow fluctuation modes has significant transfer aggregation and successive frequency, and there are significant frequent transfer modes. Strong clustering modes and large hub modes effectively characterize the trajectory characteristics of flow fluctuation evolution. These regular features provide a theoretical basis for predicting air traffic flow

fluctuations state and constructing flow management plans, which has practical significance for improving airport

capacity utilization efficiency and optimizing airport time resource allocation.

Key words:

transport aviation, complex network, air traffic flow, nonlinear time series analysis, symbolic dynamics

CLC Number:

V355

ZHANG Xie , ZHANG Jun , LIU Hongzhi , ZHAO Yifei .

Research on evolution of air traffic flow fluctuations based on integration

encoding transition network

[J]. Journal of Civil Aviation University of China, 2025, 43(2): 19-30.

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Research on evolution of air traffic flow fluctuations based on integration

encoding transition network

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