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What is TES-AC Water Load Prediction Model about?

This research develops a machine learning model using a Multilayer Perceptron to predict the water volume needed for Thermal-Energy-Storage-Air-Conditioning (TES-AC) systems in commercial buildings. By analyzing external factors such as weather, occupancy, and day of the week, the model achieves a prediction accuracy of 93.4%, assisting facility managers in optimizing energy consumption and reducing costs. The flexibility of the model allows it to be retrained for different TES-AC systems without needing sp

Author

Artric Valera Vera

Language

EN