State-of-the-art on research and applications of machine learning in the building life cycle

T Hong, Z Wang, X Luo, W Zhang - Energy and Buildings, 2020 - Elsevier
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

A review and reflection on open datasets of city-level building energy use and their applications

X Jin, C Zhang, F Xiao, A Li, C Miller - Energy and Buildings, 2023 - Elsevier
Data related to building energy use fuels the research and applications on building energy
efficiency, which is an essential measure to address global energy and environmental …

Data mining in the construction industry: Present status, opportunities, and future trends

H Yan, N Yang, Y Peng, Y Ren - Automation in Construction, 2020 - Elsevier
The construction industry is experiencing remarkable growth in the data generation. Data
mining (DM) from considerable amount of data in the construction industry has emerged as …

Occupant-centric urban building energy modeling: Approaches, inputs, and data sources-A review

S Dabirian, K Panchabikesan, U Eicker - Energy and buildings, 2022 - Elsevier
Occupant-related inputs are significant parameters that influence energy simulation
accuracy at both the building and urban levels. In most previous research works, fixed …

A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings

B Grillone, S Danov, A Sumper, J Cipriano… - … and Sustainable Energy …, 2020 - Elsevier
Increasing the energy efficiency of the built environment has become a priority worldwide
and especially in Europe. Because of the relatively low turnover rate of the existing built …

Development of an ANN-based building energy model for information-poor buildings using transfer learning

A Li, F Xiao, C Fan, M Hu - Building simulation, 2021 - Springer
Accurate building energy prediction is vital to develop optimal control strategies to enhance
building energy efficiency and energy flexibility. In recent years, the data-driven approach …

SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods

J Roth, A Martin, C Miller, RK Jain - Applied Energy, 2020 - Elsevier
Cities officials are increasingly interested in understanding spatial and temporal energy
patterns of the built environment to facilitate their city's transition to a low-carbon future. In …

Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review

B Dong, Y Liu, H Fontenot, M Ouf, M Osman, A Chong… - Applied Energy, 2021 - Elsevier
Traditional occupant behavior modeling has been studied at the building level, and it has
become an important factor in the investigation of building energy consumption. However …

Unsupervised learning of energy signatures to identify the heating system and building type using smart meter data

P Westermann, C Deb, A Schlueter, R Evins - Applied Energy, 2020 - Elsevier
A high-quality building energy retrofit analysis requires knowledge of building characteristics
like the type of installed heating system. This means auditing the building in person or …

Prediction of building power consumption using transfer learning-based reference building and simulation dataset

Y Ahn, BS Kim - Energy and Buildings, 2022 - Elsevier
With the advancements in data processing technologies and the increased use of
renewable energy systems, the development of microgrid has gained attention …