A review of machine learning in building load prediction
The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …
opportunities for applying machine learning to building energy system modeling and …
Machine learning applications in urban building energy performance forecasting: A systematic review
In developed countries, buildings are involved in almost 50% of total energy use and 30% of
global green-house gas emissions. Buildings' operational energy is highly dependent on …
global green-house gas emissions. Buildings' operational energy is highly dependent on …
A novel CNN-GRU-based hybrid approach for short-term residential load forecasting
Electric energy forecasting domain attracts researchers due to its key role in saving energy
resources, where mainstream existing models are based on Gradient Boosting Regression …
resources, where mainstream existing models are based on Gradient Boosting Regression …
Data-driven estimation of building energy consumption and GHG emissions using explainable artificial intelligence
Energy consumption prediction is an integral part of planning and controlling energy used in
the building sector which accounts for 40% of the global energy consumption and a …
the building sector which accounts for 40% of the global energy consumption and a …
A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems
The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …
application on the multivariable prediction of IES parameters have mostly been carried out …
Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality
The indoor environment directly affects health and comfort as humans spend most of the day
indoors. However, improperly controlled ventilation systems can expend unnecessary …
indoors. However, improperly controlled ventilation systems can expend unnecessary …
Machine learning for estimation of building energy consumption and performance: a review
Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
buildings are known as the foremost contributor to greenhouse gasses. Therefore …
State-of-the-art on research and applications of machine learning in the building life cycle
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 …
machine learning has been explored and applied to buildings research for the past decades …
Predicting industrial building energy consumption with statistical and machine-learning models informed by physical system parameters
The industrial sector consumes about one-third of global energy, making them a frequent
target for energy use reduction. Variation in energy usage is observed with weather …
target for energy use reduction. Variation in energy usage is observed with weather …
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) …