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

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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Bibliographic Details
Main Authors: Njogho Kenneth Tebong, Théophile Simo, Armand Nzeukou Takougang, Patrick Herve Ntanguen
Format: Article
Language:English
Published: Elsevier 2023-06-01
Series:Heliyon
Subjects:
Reservoir inflow
Ensemble deep learning
STL-Decomposition
Dense model
Conv1D
LSTM
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023036630

Internet

http://www.sciencedirect.com/science/article/pii/S2405844023036630

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