Dynamic Correlation-Based Graph Neural Network With Edge-Level Attention for Traffic Congestion Prediction
The prediction of traffic congestion is an issue of great significance for the development of intelligent traffic systems for minimizing the delays encountered during travel. In this study, a dynamic correlation-based graph learning framework for efficient traffic congestion prediction is proposed by using a Spatio-Tem...