交通运输研究2025，Vol.11Issue(6)：112-120,139,10.DOI:10.16503/j.cnki.2095-9931.2025.06.009
基于AGCN的融合运行空域网络关键节点识别方法
Identification Method of Key Nodes in Integrated Operation Airspace Networks Based on AGCN
摘要
Abstract
To identify key nodes in the integrated operational airspace involving unmanned and manned aerial vehicles,and support the safety management and network optimization of airspace,this study develops a key node identification and efficient prediction method that simultaneously characterizes the structural properties of airspace networks and the functional characteristics of traffic operations.From a structure-function coupling perspective,a weighted network efficiency index integrating global topological structure and traffic-carrying capability is constructed.By quantifying the loss rate of weighted network efficiency induced by node failures,a quantitative model for critical node importance is established,enabling a unified characterization of nodes' structural importance and operational influence.On this basis,to address the high computational complexity of critical node importance evaluation in large-scale integrated airspace networks,an attention-based graph convolutional network(AGCN)prediction model is developed to enable rapid prediction of node importance,and its performance is comparatively evaluated with convolutional neural network(CNN)and graph convolutional network(GCN)models.Experimental results demonstrate that the proposed AGCN model can accurately predict the distribution of node importance.On the test dataset,the mean absolute error(MAE)and root mean square error(RMSE)of the AGCN model are reduced by 4.04% and 6.12%,respectively,compared with the best-performing GCN model,while computational time is also significantly reduced.The results indicate that the structure-function coupled importance definition effectively captures the differential impact of node failures on overall operational efficiency in integrated airspace,and the resulting node criticality rankings exhibit both consistency and discriminability.Moreover,the AGCN model enables effective estimation of node importance with reduced computational complexity,making it suitable for key node analysis in large-scale integrated airspace operations.关键词
复杂网络/融合运行空域/关键节点识别/AGCN/网络效率Key words
complex network/integrated operation airspace/key node identification/AGCN/net-work efficiency分类
交通工程引用本文复制引用
张颖,田文,徐世民,廖鸷涵,刘明宇..基于AGCN的融合运行空域网络关键节点识别方法[J].交通运输研究,2025,11(6):112-120,139,10.基金项目
科技部国家重点研发计划项目(2022YFB4300905) （2022YFB4300905）
