A neural network-based surrogate model to predict building features from heating and cooling load signatures

S Ferreira, B Gunay, A Wills, F Rizvi - Journal of Building …, 2024 - Taylor & Francis
Addressing the challenges of scalable and cost-effective energy performance analysis in
mid to high-rise office buildings, this paper introduces a novel approach utilizing an inverse …

Research on an adaptive prediction method for restaurant air quality based on occupancy detection

Y Zhao, C **ong, L Rong, Z Luo, T Hussein… - Building and …, 2025 - Elsevier
This study evaluates the impact of personnel on air quality in air-conditioned restaurant
environments during winter, summer, and transitional seasons, characterized by the …

[HTML][HTML] Modelling district heating demand: A synthetic dataset for two residential neighbourhoods

K Ritosa, I De Jaeger, D Saelens, S Roels - Data in Brief, 2025 - Elsevier
The extensive artificial datasets developed in this study capture the energy demands of two
districts and, with reasonable constraints, emulate monitoring campaigns typically …

[PDF][PDF] From Smart Heat Meters to Diagnostics: Data-Driven Methodologies for Building Efficiency Assessment within District Heating

D Leiria - 2024 - vbn.aau.dk
Overall, this dissertation provides a foundational framework for utilizing SHM data in
buildings with other sources of data to enhance the efficiency and sustainability of DH …