STHSGCN: Spatial-temporal heterogeneous and synchronous graph convolution network for traffic flow prediction
Author:
Publisher
Elsevier BV
Subject
Multidisciplinary
Reference45 articles.
1. Deep learning on traffic prediction: methods, analysis, and future directions;Yin;IEEE Trans. Intell. Transp. Syst.,2022
2. Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction;Ali;Neural Netw.,2022
3. Hybrid spatio-temporal graph convolutional network: improving traffic prediction with navigation data;Dai,2020
4. Optimized graph convolution recurrent neural network for traffic prediction;Guo;IEEE Trans. Intell. Transp. Syst.,2021
5. A dynamical spatial-temporal graph neural network for traffic demand prediction;Huang;Inf. Sci.,2022
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