STL-decomposition ensemble deep learning models for daily reservoir inflow forecast for hydroelectricity production

Accurate reservoir inflow forecasting is crucial for efficient water management. In this study, different deep learning models, including Dense, Long short-term memory (LSTM), and one-dimensional convolutional neural networks (Conv1D), were used to build ensembles. Seasonal-trend decomposition using...

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Detalles Bibliográficos
Autores principales: Tebong, Njogho Kenneth, Simo, Théophile, Takougang, Armand Nzeukou, Ntanguen, Patrick Herve
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248095/
https://www.ncbi.nlm.nih.gov/pubmed/37303512
http://dx.doi.org/10.1016/j.heliyon.2023.e16456

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248095/
https://www.ncbi.nlm.nih.gov/pubmed/37303512
http://dx.doi.org/10.1016/j.heliyon.2023.e16456

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