Occupant-Aware Energy Consumption Prediction in Smart Buildings Using a LSTM Model and Time Series Data

Occupant-Aware Energy Consumption Prediction in Smart Buildings Using a LSTM Model and Time Series Data

Accurate energy consumption prediction in commercial buildings is a challenging research task. Energy prediction plays a crucial role in energy efficiency, management, planning, sustainability, risk management, diagnosis, and demand response. Although many studies have been conducted on building ene...

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Bibliographic Details
Main Authors: Muhammad Anan, Khalid Kanaan, Driss Benhaddou, Nidal Nasser, Basheer Qolomany, Hanaa Talei, Ahmad Sawalmeh
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Energies
Subjects:
ARIMA
LSTM
forecast
energy consumption
machine learning
Online Access:https://www.mdpi.com/1996-1073/17/24/6451
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