Transforming Building Energy Management: Sparse, Interpretable, and Transparent Hybrid Machine Learning for Probabilistic Classification and Predictive Energy Modelling

Transforming Building Energy Management: Sparse, Interpretable, and Transparent Hybrid Machine Learning for Probabilistic Classification and Predictive Energy Modelling

The building sector, responsible for 40% of global energy consumption, faces increasing demands for sustainability and energy efficiency. Accurate energy consumption forecasting is essential to optimise performance and reduce environmental impact. This study introduces a hybrid machine learning fram...

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Bibliographic Details
Main Authors: Yiping Meng, Yiming Sun, Sergio Rodriguez, Binxia Xue
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Architecture
Subjects:
hybrid machine learning
sparse interpretable transparent (SIT) model
energy prediction
uncertainty quantification
sustainable energy management
Online Access:https://www.mdpi.com/2673-8945/5/2/24
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