Control mechanisms for heating, ventilation and air conditioning in buildings follow set parameters to make conditions in a building more comfortable, but what they save on time can reduce efficiency and increase energy costs, according to Gregory Pavlak, assistant professor of architectural engineering. More sophisticated control models, known as model predictive controllers, can optimize multiple variables to save on energy, operating costs and carbon emissions but can require much more time to find solutions.
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Machine learning offers shortcut to optimal HVAC operation
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