Probabilistic deep learning models using multimodal building and weather data deliver 18.8% and 27.6% lower RMSE than ResStock for building-level heating and electricity forecasts, with 59% better WIS.
En- hancing hourly heat demand prediction through artificial neural networks: A national level case study,
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Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models
Probabilistic deep learning models using multimodal building and weather data deliver 18.8% and 27.6% lower RMSE than ResStock for building-level heating and electricity forecasts, with 59% better WIS.