Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation
Sustainable forecasting of home energy demand (SFHED) is crucial for promoting energy efficiency, minimizing environmental impact, and optimizing resource allocation. Machine learning (ML) supports SFHED by identifying patterns and forecasting demand. However, conventional hyperparameter tuning meth...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546825001168 |
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