Memory-Augmented Spatio-Temporal Transformer for Robust Traffic Flow Forecasting

Accurate traffic flow prediction plays a critical role in intelligent transportation systems, supporting traffic management, congestion mitigation, and efficient utilization of road resources. Advances in neural network-based methods, particularly graph neural networks (GNNs) and attention-based mod...

Celý popis

Podrobná bibliografie

Hlavní autoři:	Puqing Hu, Chunjiang Wu, Chen Wang, Xin Yang, Zhibin Li, Tinghui Chen, Shijie Zhou
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2026-03-01
Edice:	Biomimetics
Témata:	traffic flow forecasting spatio-temporal representation learning graph attention networks long-term temporal dependencies neural prediction models
On-line přístup:	https://www.mdpi.com/2313-7673/11/3/170
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!