Forecasting Residential Energy Consumption with the Use of Long Short-Term Memory Recurrent Neural Networks

Forecasting Residential Energy Consumption with the Use of Long Short-Term Memory Recurrent Neural Networks

In the quest to improve energy efficiency in residential environments, home energy management systems (HEMSs) have emerged as an effective solution, leveraging artificial intelligence (AI) technologies to improve energy efficiency. This study proposes a deep learning-based approach employing Long Sh...

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Bibliographic Details
Main Authors: Zurisaddai Severiche-Maury, Carlos Eduardo Uc-Rios, Wilson Arrubla-Hoyos, Dora Cama-Pinto, Juan Antonio Holgado-Terriza, Miguel Damas-Hermoso, Alejandro Cama-Pinto
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Energies
Subjects:
HEMS
energy consumption prediction
deep learning
LSTM
networks
smart home energy efficiency
Online Access:https://www.mdpi.com/1996-1073/18/5/1247
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