研究机场交通流量的波动范围特征是进行高效流量管理及控制的基础，理解并掌握机场交通流量波动范围特征对维持整个机场交通运行的稳定性和有效性起着重要作用。通过考虑时间的不可逆性及在一定时段内机场流量大于设施容量所产生的拥堵量会累加影响在后续时间点上，提出自适应跨越网络的构建方法。从复杂网络拓扑特性角度出发，对网络的整体特征以及节点中心性进行分析，并应用独立性权系数法分别计算节点的综合中心度，识别网络中的强波动核心枢纽时间节点。结果表明：根据北京大兴机场流量数据映射得到的自适应跨越网络呈现复杂有序的特点，具有无标度特征，网络是同配的且有明显的社团结构；21：20—22：25（节点257 ~ 269）中在各中心度的排名均靠前，波动影响范围较大，属于网络中的核心枢纽节点；综合中心度归纳了网络的各种拓扑中心性特征，并对其进行定量分析后有效刻画了网络中的强波动节点。该方法为机场交通流量的优化管理和异常波动研究提供了理论依据和实践参考，为提升机场运行效率和安全性提供了新的视角。

Studying the characteristics of airport traffic flow fluctuation range is fundamental for efficient traffic management and control. Mastering these characteristics plays a crucial role in maintaining the stability and effectiveness of overall airport operations. Considering the irreversibility of time and the cumulative impact of traffic congestion, which occurs when airport traffic exceeds facility capacity within certain time intervals, a method for constructing an adaptive crossing network was proposed. From the perspective of complex network topology, both the overall characteristics of the network and the centrality of nodes were analyzed. The integrated centrality of nodes was calculated using the independent weighting coefficient method, enabling the identification of key time nodes that are core hubs of strong fluctuations within the network. The results show that the adaptive crossing network, mapped based on the traffic data from Beijing Daxing International Airport, exhibits characteristics of complexity and order, featuring scale-free properties, assortativity, and a distinct community structure. The time period from 21:20 to 22:25 (nodes 257 ~ 269) ranks highly across various centrality measures, indicating a significant fluctuation impact range, and thus, these nodes are identified as core hub nodes within the network. The integrated centrality synthesizes various topological centrality features of the network, and through quantitative analysis, effectively characterizes the strong fluctuation nodes within the network. This method provides a theoretical basis and practical reference for the optimization of airport traffic flow management and the study of abnormal fluctuations, offering a new perspective for enhancing airport operational efficiency and safety.