基于融合编码转移网络的空中交通流量波动演化研究  

Research on evolution of air traffic flow fluctuations based on integration encoding transition network

作　　者：张勰[1] 张钧 刘宏志 赵嶷飞[1] ZHANG Xie;ZHANG Jun;LIU Hongzhi;ZHAO Yifei(College of Air Traffic Management,CAUC,Tianjin 300300,China;Research Institute of Civil Aviation Development and Planning,China Academy of Civil Aviation Science and Technology,Beijing 100028,China)

机构地区：[1]中国民航大学空中交通管理学院,天津300300 [2]中国民航科学研究院民航发展规划研究院,北京100028

出　　处：《中国民航大学学报》2025年第2期19-30,共12页Journal of Civil Aviation University of China

基　　金：国家自然科学基金项目(U1633112,U2133210)。

摘　　要：为突破以往仅针对空中交通流量波动方向的研究局限,考虑在空中交通流动态演化研究中充分突出流量波动状态与机场容量限制等实际运行信息,借助动态粗粒化编码方法将机场流容比及流量波动梯度进行符号编码并融合为波动模态,提出了融合编码转移网络构建方法。针对北京大兴国际机场(简称大兴机场)的全天时段与协调时段,从复杂网络视角开展了空中交通流量波动演化规律与特征的定量分析与定性识别研究。研究结果表明:大兴机场两个时段的空中交通流量波动演化差异主要集中在宏观层面;流量波动模态的演化具有显著的转移集聚与相继频现的特点,存在显著的频繁转移模式;强聚类模态和大枢纽模态有效刻画了流量波动演化的轨迹性特征。这些规律性特征为空中交通流量波动状态预测、流量管理预案构建提供了理论基础,对提升机场容量使用效率、优化机场时刻资源配置具有现实意义。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.

关 键 词：航空运输 复杂网络 空中交通流量 非线性时间序列分析 符号动力系统 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]