Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
[HTML][HTML] Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
A comparative study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in estimating the heating load of buildings' energy efficiency for smart city planning
Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for
optimizing smart cities planning. This study proposed four new artificial intelligence (AI) …
optimizing smart cities planning. This study proposed four new artificial intelligence (AI) …
Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0
Industry 4.0 promotes the transformation of manufacturing industry to intelligence, which
demands advances in materials, devices, and systems of the construction industry …
demands advances in materials, devices, and systems of the construction industry …
Systematic review of deep learning and machine learning for building energy
S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …
smart cities. Recently, the novel data science and data-driven technologies have shown …
[HTML][HTML] Advances of machine learning in multi-energy district communities‒mechanisms, applications and perspectives
Y Zhou - Energy and AI, 2022 - Elsevier
Energy paradigm transition towards the carbon neutrality requires combined and continuous
efforts in cleaner power production, advanced energy storages, flexible district energy …
efforts in cleaner power production, advanced energy storages, flexible district energy …
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Implementing machine-learning models in real applications is crucial to achieving intelligent
building control and high energy efficiency. Over the past few decades, numerous studies …
building control and high energy efficiency. Over the past few decades, numerous studies …
A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine
Z Gao, J Yu, A Zhao, Q Hu, S Yang - Energy, 2022 - Elsevier
Air conditioning system is extensively used in large commercial buildings. The fast and
accurate building cooling load forecasting is the basis for improving the operation efficiency …
accurate building cooling load forecasting is the basis for improving the operation efficiency …
Buildings' energy consumption prediction models based on buildings' characteristics: Research trends, taxonomy, and performance measures
Building's energy consumption prediction is essential to achieve energy efficiency and
sustain-ability. Building's energy consumption is highly dependent on buildings' …
sustain-ability. Building's energy consumption is highly dependent on buildings' …
[HTML][HTML] Predicting energy consumption for residential buildings using ANN through parametric modeling
E Elbeltagi, H Wefki - Energy Reports, 2021 - Elsevier
Controlling buildings energy consumption is a great practical significance. During early
design stage, accurate and rapid prediction of energy consumption could provide a …
design stage, accurate and rapid prediction of energy consumption could provide a …