Effective management of energy consumption during the COVID-19 pandemic: The role of ICT solutions

W Strielkowski, I Firsova, I Lukashenko… - Energies, 2021‏ - mdpi.com
This research tackles effective and functional management practices in energy consumption
using advanced technological solutions to mitigate unexpected events. This study …

Investigating the performance of machine learning models combined with different feature selection methods to estimate the energy consumption of buildings

X Liu, H Tang, Y Ding, D Yan - Energy and Buildings, 2022‏ - Elsevier
Abstract Machine learning is considered a promising method for develo** building energy-
benchmarking models. However, the high dimensionality of building energy datasets can …

EnergyStar++: Towards more accurate and explanatory building energy benchmarking

P Arjunan, K Poolla, C Miller - Applied Energy, 2020‏ - Elsevier
Building energy performance benchmarking has been adopted widely in the USA and
Canada through the Energy Star Portfolio Manager platform. Building operations and energy …

Investigating the nexus between environmental information disclosure and green development efficiency: The intermediary role of green technology innovation—a …

H Yuan - Journal of the Knowledge Economy, 2024‏ - Springer
This study investigates the intricate relationship between environmental information
disclosure (EID) and green development efficiency (GDE) in Chinese cities from 2005 to …

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 …

Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking

A Andrews, RK Jain - Applied Energy, 2022‏ - Elsevier
The intermittency of carbon-free renewables and the demand changes associated with the
widespread push for electrifying the transportation and building sectors provides an …

[HTML][HTML] Building energy loads prediction using bayesian-based metaheuristic optimized-explainable tree-based model

BA Salami, SI Abba, AA Adewumi, UA Dodo… - Case Studies in …, 2023‏ - Elsevier
The study presents a sophisticated hybrid machine learning methodology tailored for
predicting energy loads in occupied buildings. Leveraging eight pivotal input features …

Energy consumption prediction and energy-saving suggestions of public buildings based on machine learning

C Chen, Z Gao, X Zhou, M Wang, J Yan - Energy and Buildings, 2024‏ - Elsevier
Energy consumption prediction can help the government to formulate building energy
consumption quotas and buildings energy consumption correlation analysis can provide a …

Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature

MM Abdelrahman, S Zhan, C Miller, A Chong - Energy and Buildings, 2021‏ - Elsevier
The ever-changing data science landscape is fueling innovation in the built environment
context by providing new and more effective means of converting large raw data sets into …

Exploring the influence of urban context on building energy retrofit performance: A hybrid simulation and data-driven approach

A Nutkiewicz, B Choi, RK Jain - Advances in Applied Energy, 2021‏ - Elsevier
Cities are an integral part to meeting the world's sustainable energy goals. Specifically,
retrofits have been implemented to improve energy efficiency and reduce carbon emissions …