火力与指挥控制2025，Vol.50Issue(2)：13-20,8.DOI:10.3969/j.issn.1002-0640.2025.02.002
基于图神经网络的天地一体化网络建模及性能预测
Modeling and Performance Prediction of Space-integrated-Ground Network Based on Graph Neural Network
摘要
Abstract
With the continuous emergence of new combat forces,the land air defense command and control network has shown a trend of space-integrated-ground,and the increase in combat elements has put forward higher requirements for the low-delay and low-jitter transmission capabilities of command and control network services.To address the difficulties of accurately constraining the complex characteristics of traffic and modeling in heterogeneously integrated network,a network performance prediction model based on the fusion of graph neural networks and attention mechanisms is proposed to achieve accurate prediction of traffic transmission delay and jitter performance in the integrated air defense command and control network.Experiments have shown that the model has good predictive performance for air defense ground combat command and control traffic.关键词
网络性能预测/天地一体化/图神经网络/深度学习Key words
network performance prediction/space-integrated-ground/graph neural network/deep learning分类
计算机与自动化引用本文复制引用
潘成胜,沈凌宇,赵晨,崔骁松..基于图神经网络的天地一体化网络建模及性能预测[J].火力与指挥控制,2025,50(2):13-20,8.基金项目
国家自然科学基金资助项目(61931004) （61931004）
