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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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Principais autores: Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen
Format: Artigo
Sprog:Inglês
Udgivet: Nature Portfolio 2024-12-01
Serier:Scientific Reports
Fag:
Precipitation forecasting
CEEMDAN-GRU
Complete ensemble empirical mode decomposition with adaptive noise
Gated recurrent unit
Time series prediction
Online adgang:https://doi.org/10.1038/s41598-024-83365-9
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