Water Flow Forecasting Based on River Tributaries Using Long Short-Term Memory Ensemble Model

Water Flow Forecasting Based on River Tributaries Using Long Short-Term Memory Ensemble Model

Water flow forecasts are an essential information for energy production, management and hydropower control. Advanced actions to optimize electricity production can be taken based on predicted information. This work proposes an ensemble strategy using recurrent neural networks to generate a forecast...

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Bibliographic Details
Main Authors: Diogo F. Costa Silva, Arlindo R. Galvão Filho, Rafael V. Carvalho, Filipe de Souza L. Ribeiro, Clarimar J. Coelho
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Energies
Subjects:
water flow forecasting
energy
ensemble model
long short-term memory
LSTM
Online Access:https://www.mdpi.com/1996-1073/14/22/7707

Internet

https://www.mdpi.com/1996-1073/14/22/7707

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