Dual-Gated Graph Convolutional Recurrent Unit with Integrated Graph Learning (DG3L): A Novel Recurrent Network Architecture with Dynamic Graph Learning for Spatio-Temporal Predictions

Dual-Gated Graph Convolutional Recurrent Unit with Integrated Graph Learning (DG3L): A Novel Recurrent Network Architecture with Dynamic Graph Learning for Spatio-Temporal Predictions

Spatio-temporal prediction is crucial in intelligent transportation systems (ITS) to enhance operational efficiency and safety. Although Transformer-based models have significantly advanced spatio-temporal prediction performance, recent research underscores the importance of learning dynamic spatio-...

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Bibliographic Details
Main Authors: Yuxuan Wang, Zhouyuan Zhang, Shu Pi, Haishan Zhang, Jiatian Pi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Entropy
Subjects:
graph learning
spatio-temporal prediction
Graph Convolutional Network
Gated Recurrent Unit
attention mechanism
Online Access:https://www.mdpi.com/1099-4300/27/2/99
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