@inproceedings{e7f1f66dfe5a481aac5acfb594f2ed50,
title = "COMPARATIVE MACHINE LEARNING AND DEEP LEARNING STUDY OF ENERGY PREDICTIONS IN URBAN AND RURAL BUILDINGS",
abstract = "The European Union{\textquoteright}s (EU) 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.",
keywords = "building energy modeling, deep learning, Energy Performance Certificates, machine learning, retrofitting simulation",
author = "Sharon Coffee and James O{\textquoteright}donnell and Cathal Hoare",
note = "Publisher Copyright: {\textcopyright} 2025, European Council on Computing in Construction (EC3). All rights reserved.; European Conference on Computing in Construction, EC3 2025 and 42nd International CIB W78 Conference on IT in Construction, 2025 ; Conference date: 14-07-2025 Through 17-07-2025",
year = "2025",
doi = "10.35490/EC3.2025.326",
language = "English",
isbn = "9789083451312",
series = "Proceedings of the European Conference on Computing in Construction",
publisher = "European Council on Computing in Construction (EC3)",
editor = "Ekaterina Petrova and Marijana Sre{\'c}kovi{\'c} and Pedro Meda and Soman, \{Ranjith K.\} and Daniel Hall and Jakob Beetz and Jenn McArthur",
booktitle = "Proceedings of the 2025 European Conference on Computing in Construction and 42nd International CIB W78 Conference on Information Technology in Construction, 2025",
}