[HTML][HTML] Review of non-domestic building stock modelling studies under socio-technical system framework

J Zhou, P Fennell, I Korolija, Z Fang, R Tang… - Journal of Building …, 2024 - Elsevier
The construction industry contributes to approximately 30% of global energy consumption
and carbon dioxide emissions, necessitating urgent measures to mitigate carbon emissions …

[HTML][HTML] A holistic time series-based energy benchmarking framework for applications in large stocks of buildings

MS Piscitelli, R Giudice, A Capozzoli - Applied Energy, 2024 - Elsevier
With the proliferation of Internet of Things (IoT) sensors and metering infrastructures in
buildings, external energy benchmarking, driven by time series analytics, has assumed a …

[HTML][HTML] CC-GAIN: Clustering and classification-based generative adversarial imputation network for missing electricity consumption data imputation

J Hwang, D Suh - Expert Systems with Applications, 2024 - Elsevier
The widespread use of data across various fields has made missing data imputation
technology a crucial tool. High-quality data is essential for effective energy management in …

A Survey on the Use of Synthetic Data for Enhancing Key Aspects of Trustworthy AI in the Energy Domain: Challenges and Opportunities

M Meiser, I Zinnikus - Energies, 2024 - mdpi.com
To achieve the energy transition, energy and energy efficiency are becoming more and
more important in society. New methods, such as Artificial Intelligence (AI) and Machine …

Special issue on artificial intelligence in thermal engineering systems

F **ao, F Guo, C Fan, G Besagni - Applied Thermal Engineering, 2024 - Elsevier
The special issue “AI in Thermal Engineering” covers the most recent studies with a focus on
the applications of artificial intelligence (AI) technologies in thermal engineering systems …

[HTML][HTML] Continual learning for energy management systems: A review of methods and applications, and a case study

AN Sayed, Y Himeur, I Varlamis, F Bensaali - Applied Energy, 2025 - Elsevier
An intelligent system must incrementally acquire, update, accumulate, and exploit
knowledge to navigate the real world's intricacies. This trait is frequently referred to as …

Signal separation and continuous missing value imputation of strain gauge in the icebreaker sensor system

HB Heo, EJ Oh, SH Park - Applied Ocean Research, 2024 - Elsevier
Korea's first icebreaking research vessel, ARAON, has been conducting icebreaking
performance tests in polar waters since 2010. These tests collect data to calculate design …

Gap filling crowdsourced air temperature data in cities using data-driven approaches

M He, Z Luo, X **e, P Wang, H Wang… - Building and …, 2025 - Elsevier
Crowdsourced temperature data from citizen weather stations (CWS) in urban area offer
valuable insights into intra-urban heat distribution but are often challenged by a significant …

[HTML][HTML] Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight

A Liguori, M Quintana, C Fu, C Miller, J Frisch… - Energy and …, 2024 - Elsevier
Missing data are frequently observed by practitioners and researchers in the building energy
modeling community. In this regard, advanced data-driven solutions, such as Deep Learning …

Statistical jump model for mixed-type data with missing data imputation

FP Cortese, A Pievatolo - arxiv preprint arxiv:2409.01208, 2024 - arxiv.org
In this paper, we address the challenge of clustering mixed-type data with temporal
evolution by introducing the statistical jump model for mixed-type data. This novel framework …