Dynamic Graph Transformer with Spatio-Temporal Attention for Streamflow Forecasting

Accurate streamflow forecasting is crucial for water resources management and flood mitigation, yet it remains challenging due to the complex dynamics of hydrological systems. Conventional data-driven approaches often struggle to effectively capture spatio-temporal evolution characteristics, particu...

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Autores principales:	Bo Li, Qingping Li, Xinzhi Zhou, Mingjiang Deng, Hongbo Ling
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2025-12-01
Colección:	Hydrology
Materias:	streamflow forecasting graph attention mechanism transformer model spatio-temporal attention mechanism deep learning (DL) hydrological time series forecasting
Acceso en línea:	https://www.mdpi.com/2306-5338/12/12/322
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