In our project, we aim to identify areas of inefficient energy consumption for buildings on the UC Berkeley campus. We used artificial neural networks to forecast the energy demand for all buildings. By comparing the predicted to the actual consumption, areas of inefficient energy use are identified. This empowers campus facilities to make more informed decisions on how to save energy across campus.
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