机场的进离场空中交通流复杂性

机场进离场空中交通流复杂性的量化是空管和机场进行预测和管控的重要依据。提出基于排列熵的复杂熵因果平面(complexity entropy causality plane, CECP)以及Fisher-Shannon(FS)因果平面的机场进离场空中交通流复杂性量化分析模型，量化单机场进离场空中交通流量复杂度，研究多机场进离场空中交通流复杂度之间的关联性。针对单机场，首先将机场进离场空中交通流量时间序列符号化，计算时间序列的标准排列熵和统计复杂度以及Fisher信息，量化机场进离场空中交通流时间序列的复杂程度；针对多机场，构建CECP以及FS,分析比较各机场在CECP和FS中的位置，区分进离场空中交通流复杂性较高的机场。验证结果表明：提出的模型对于量化机场进离场空中交通流复杂性具有可行性和准确性，可以有效区分进离场空中交通流复杂程度较高的机场，对机场交通流的实时预测和管控具有指导意义。

Research On The Complexity Of Air traffic flow In Arrivals And Departures Of Airports

The quantification of airport approach and departure air traffic flow complexity is an important basis for ATC and airport prediction and control. In this paper, we propose a model for quantifying the complexity of airport approach and departure air traffic flows based on the Complex Entropy Causality Plane (CECP) and the Fisher-Shannon Causality Plane (FS) to quantify the complexity of approach and departure air traffic flows at single airports and to investigate the correlation between the complexity of approach and departure air traffic flows at multiple airports. For single airports, the time series of airport approach and departure air traffic flow is firstly symbolized, and the standard alignment entropy and statistical complexity of the time series as well as the Fisher information are calculated to quantify the complexity of the time series of airport approach and departure traffic; for multiple airports, the complexity entropy causal plane and Fisher-Shannon causal plane are constructed to analyze the position of each airport in the CECP and FS diagrams The proposed model can be used to distinguish airports with high complexity of approach and departure air traffic flows. The validation results show that the proposed model is feasible and accurate for quantifying the complexity of airport approach and departure air traffic flows, and can effectively distinguish airports with high complexity of approach and departure air traffic flows, which is of guidance for real-time prediction and control of airport air traffic flows.