Predicting Indoor Temperature using Machine Learning

Using the ecobee thermostat data from sixteen Canadian and US houses, the prediction accuracy of the generalized regression neural network (GRNN) algorithm and the resilient back propagation neural network (ANN) algorithm were evaluated. The physical range of this model encompasses a single building.

D. Yu, A. Abhari, A.S. Fung, K. Raahemifar, F. Mohammadi, “Predicting indoor temperature from smart thermostat and weather forecast data”, Proceedings of the Communications and Networking Symposium, Baltimore, 2018. https://dl.acm.org/doi/10.5555/3213200.3213209

residential building demand, load forecasting

outdoor temperature, solar radiation, thermostat temperature setpoints, humidity, heating and cooling durations, fan duration

indoor temperature