Comparative Machine Learning and Deep Learning Study of Energy Predictions in Urban and Rural Buildings

Abstract: The EU’s energy targets highlight the importance of retrofitting older buildings to reduce carbon emissions. However, many rural properties remain in the lowest energy rating categories, complicating retrofitting efforts. Urban buildings dominate Energy Performance Certificates (EPC) models, while rural structures require tailored approaches due to their diversity and lower energy performance. This research compares machine and deep learning models to address gaps in predictive accuracy and scalability in retrofitting simulations. The methodology predicts EPC ratings based on renovation policies and improves regional segmentation and archetype classifications. These strategies offer insights for rural residential buildings aligned with EU energy efficiency standards.