GTGCN: A gated temporal-graph coupling network model based on contrastive learning for traffic prediction.
- DOI
- 10.1016/j.neunet.2026.109060
- Published
- 2026 Oct
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109060,
title = {GTGCN: A gated temporal-graph coupling network model based on contrastive learning for traffic prediction.},
author = {Yang S and Huang C and Yin K and Zhang H},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109060},
url = {https://doi.org/10.1016/j.neunet.2026.109060}
}RIS
TY - JOUR TI - GTGCN: A gated temporal-graph coupling network model based on contrastive learning for traffic prediction. AU - Yang S AU - Huang C AU - Yin K AU - Zhang H PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109060 UR - https://doi.org/10.1016/j.neunet.2026.109060 ER -
APA
S, Y., C, H., K, Y., & H, Z. (2026). GTGCN: A gated temporal-graph coupling network model based on contrastive learning for traffic prediction.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109060
Source records
- pubmed · retrieved 2026-09-26T14:58:51.450Z