A Novel Coupled Model for Monthly Rainfall Prediction Based on ESMD-EWT-SVD-LSTM
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11269-024-03815-x.pdf
Reference40 articles.
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3. Bakhshi Ostadkalayeh F, Moradi S, Asadi A, Moghaddam Nia A, Taheri S (2023) Performance improvement of LSTM-based deep learning model for streamflow forecasting using Kalman filtering. Water Resour Manag 37(8):3111–3127. https://doi.org/10.1007/s11269-023-03492-2
4. Byun J, Jun C, Kim J, Cha J, Narimani R (2023) Deep learning-based rainfall prediction using cloud image analysis. IEEE Trans Geosci Remote Sens 61:1–11. https://doi.org/10.1109/TGRS.2023.3263872
5. Chadalawada J, Havlicek V, Babovic V (2017) A genetic programming approach to system identification of rainfall-runoff models. Water Resour Manag 31:3975–3992. https://doi.org/10.1007/s11269-017-1719-1
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