舰船电子工程2024，Vol.44Issue(5)：36-40,5.DOI:10.3969/j.issn.1672-9730.2024.05.008
基于图卷积的动态航线网络链路预测模型研究
Research on Dynamic Route Network Link Prediction Model Based on Graph Convolution
摘要
Abstract
In order to overcome the limitations of traditional link prediction models in route networks,a dynamic route net-work link prediction model based on graph convolutional network(GCN)is proposed,taking into account network topology and time characteristics.This paper aggregates node and neighborhood information through graph convolution and graph pooling oper-ates,updates node feature representations,and identifies potential connections between nodes.Experiments have shown that the GCN model has higher prediction accuracy,efficiency,and performance stability compared to traditional link prediction models,making it an effective tool for dynamic route network link prediction.关键词
航空运输/链路预测/图卷积网络/动态航线网络/航线预测Key words
air transportation/link prediction/graph convolution network/dynamic route network/route prediction分类
交通工程引用本文复制引用
赵联政,张培文,黎砾丹..基于图卷积的动态航线网络链路预测模型研究[J].舰船电子工程,2024,44(5):36-40,5.基金项目
国家自然科学基金项目(编号:U2033213,U1733127) （编号:U2033213,U1733127）
中央高校基本科研业务费专项资金项目(编号:J2022-041)资助. （编号:J2022-041）
