Principles, research status, and prospects of feature engineering for data-driven building energy prediction: A comprehensive review
With the rapid growth in the volume of relevant and available data, feature engineering is
emerging as a popular research subject in data-driven building energy prediction owing to …
emerging as a popular research subject in data-driven building energy prediction owing to …
A review of deep learning techniques for forecasting energy use in buildings
J Runge, R Zmeureanu - Energies, 2021 - mdpi.com
Buildings account for a significant portion of our overall energy usage and associated
greenhouse gas emissions. With the increasing concerns regarding climate change, there …
greenhouse gas emissions. With the increasing concerns regarding climate change, there …
Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm
XJ Luo, LO Oyedele - Advanced Engineering Informatics, 2021 - Elsevier
The real-world building can be regarded as a comprehensive energy engineering system;
its actual energy consumption depends on complex affecting factors, including various …
its actual energy consumption depends on complex affecting factors, including various …
A hybrid multi-objective optimizer-based model for daily electricity demand prediction considering COVID-19
Electricity consumption has been affected due to worldwide lockdown policies against
COVID-19. Many countries have pointed out that electricity supply security during the …
COVID-19. Many countries have pointed out that electricity supply security during the …
The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods
In recent years, machine learning models based on big data have been introduced into
marketing in order to transform customer data into meaningful insights and to make strategic …
marketing in order to transform customer data into meaningful insights and to make strategic …
One month-ahead forecasting of mean daily global solar radiation using time series models
B Belmahdi, M Louzazni, A El Bouardi - Optik, 2020 - Elsevier
Accurate forecasting's of solar radiation are crucial to quantifying future solar power
production or integration. The integration of solar energy into the electricity grid has become …
production or integration. The integration of solar energy into the electricity grid has become …
[HTML][HTML] Distributed model predictive control of buildings and energy hubs
Abstract Model predictive control (MPC) strategies can be applied to the coordination of
energy hubs to reduce their energy consumption. Despite the effectiveness of these …
energy hubs to reduce their energy consumption. Despite the effectiveness of these …
A review of data-driven building energy prediction
H Liu, J Liang, Y Liu, H Wu - Buildings, 2023 - mdpi.com
Building energy consumption prediction has a significant effect on energy control, design
optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID …
optimization, retrofit evaluation, energy price guidance, and prevention and control of COVID …
[HTML][HTML] Enhancing hourly heat demand prediction through artificial neural networks: A national level case study
Meeting the goal of zero emissions in the energy sector by 2050 requires accurate
prediction of energy consumption, which is increasingly important. However, conventional …
prediction of energy consumption, which is increasingly important. However, conventional …
Estimating dynamic solar gains from on-site measured data: An ARX modelling approach
On-site measured data in combination with statistical methods is used more and more to
assess the actual performance of a building and to develop simplified models that can be …
assess the actual performance of a building and to develop simplified models that can be …