Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm

Abstract Precipitation forecasting is vital for managing disasters, urban traffic, and agriculture. This study develops an improved model for short-term precipitation forecasting by combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Gated Recurrent Unit (GRU)....

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Detalles Bibliográficos

Principais autores:	Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen
Formato:	Artigo
Idioma:	Inglês
Publicado:	Nature Portfolio 2024-12-01
Series:	Scientific Reports
Assuntos:	Precipitation forecasting CEEMDAN-GRU Complete ensemble empirical mode decomposition with adaptive noise Gated recurrent unit Time series prediction
Acceso en liña:	https://doi.org/10.1038/s41598-024-83365-9
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