Abstract
This research paper presents a concise and factual analysis of energy consumption patterns at Mbarara University of Science and Technology (MUST) based on historical data from the calendar year 2019. The study focused on the interplay between the academic calendar and energy usage, revealing variations in energy demand. Key findings emphasize the necessity for tailored energy management strategies to accommodate these fluctuations. We introduced a linear regression model for precise energy predictions, highlighting the potential for future refinement. The research offers valuable insights into data-driven energy optimization at the institution, with implications for sustainability and cost-effectiveness.
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