Artificial intelligence-based strategies for sustainable energy planning and electricity demand estimation: A systematic review
Access to electricity is a cornerstone for sustainable development and is pivotal to a
country's progress. The absence of electricity impedes development and elevates poverty …
country's progress. The absence of electricity impedes development and elevates poverty …
A comprehensive review of critical analysis of biodegradable waste PCM for thermal energy storage systems using machine learning and deep learning to predict …
This article explores the use of phase change materials (PCMs) derived from waste, in
energy storage systems. It emphasizes the potential of these PCMs in addressing concerns …
energy storage systems. It emphasizes the potential of these PCMs in addressing concerns …
Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation
Building energy prediction and management has become increasingly important in recent
decades, driven by the growth of Internet of Things (IoT) devices and the availability of more …
decades, driven by the growth of Internet of Things (IoT) devices and the availability of more …
Hybrid intelligent deep learning model for solar radiation forecasting using optimal variational mode decomposition and evolutionary deep belief network-online …
T Peng, Y Li, ZZ Song, Y Fu, MS Nazir… - Journal of Building …, 2023 - Elsevier
Accurate prediction of solar radiation is of great significance to improve the utilization of
solar energy for photovoltaic power generation on the roofs of urban buildings. Therefore, a …
solar energy for photovoltaic power generation on the roofs of urban buildings. Therefore, a …
Thermal modeling for control applications of 60,000 homes in North America using smart thermostat data
As smart thermostats become increasingly available in residential buildings, there is an
opportunity to use measured building data to calibrate models for community and district …
opportunity to use measured building data to calibrate models for community and district …
Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data
Energy demand from the built environment is among the most important contributors to
greenhouse gas emissions. One promising way to curtail these emissions is through …
greenhouse gas emissions. One promising way to curtail these emissions is through …
Improving the out-of-sample generalization ability of data-driven chiller performance models using physics-guided neural network
Modeling of the chiller performance is essential for the implementation of optimal energy-
efficient control strategies in a heating, ventilation, and air conditioning (HVAC) system …
efficient control strategies in a heating, ventilation, and air conditioning (HVAC) system …
Creating synthetic energy meter data using conditional diffusion and building metadata
Advances in machine learning and increased computational power have driven progress in
energy-related research. However, limited access to private energy data from buildings …
energy-related research. However, limited access to private energy data from buildings …
[HTML][HTML] Integrating urban building energy modeling (UBEM) and urban-building environmental impact assessment (UB-EIA) for sustainable urban development: A …
Y Li, H Feng - Renewable and Sustainable Energy Reviews, 2025 - Elsevier
Rapid urbanization has increased energy demand and environmental impacts in urban
buildings, highlighting the need to understand building interactions and energy transfer. This …
buildings, highlighting the need to understand building interactions and energy transfer. This …
A critical perspective on current research trends in building operation: Pressing challenges and promising opportunities
Despite the development of increasingly efficient technologies and the ever-growing amount
of available data from Building Automation Systems (BAS) and connected devices, buildings …
of available data from Building Automation Systems (BAS) and connected devices, buildings …