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This study presents a robust data-driven framework for forecasting energy consumption across multiple building sites using deep learning, specifically Long Short-Term Memory (LSTM) networks. Leveraging the publicly available BDG2 dataset, which integrates hourly electricity consumption, meteorological conditions, and building metadata.
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19
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