Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models

Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models

Optimization of energy consumption in urban infrastructures is essential to achieve sustainability and reduce environmental impacts. In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency impro...

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Bibliographic Details
Main Authors: Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
energy consumption forecasting
regression analysis
artificial intelligence
machine learning
supervised learning
predictive modeling
Online Access:https://www.mdpi.com/1996-1073/18/14/3672
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