The use of machine learning to determine moisture recovery in a heat wheel and its impact on indoor moisture
Highlights
• This study models moisture recovery in a heat wheel using machine learning algorithms. The moisture recovery model accounts for different possible causality leading to moisture transfer for the heat wheel.
• Yearly moisture recovery efficiencies with a 95% confidence interval and indoor RH for different rooms in a high (2-min) time resolution are revealed for a single-family house.
• The effects of the moisture recovery in the heat wheel on the indoor RH are assessed.