Research on Dynamic Route Network Link Prediction Model Based on Graph Convolution
ZHAO Lianzheng
ZHANG Peiwen
LI Lidan
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.
Keywords：air transportationlink predictiongraph convolution networkdynamic route networkroute prediction
Publication Date：2024-05-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 36-40 )