This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …

This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …

Traditional electricity is produced from coal, mineral oil, or fossil fuels those have produced a
heavy environmental pollution by the greenhouse gas emissions and industrial pollutants …

Wind energy has emerged as a highly promising source of renewable energy in recent
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …

European buildings are producing a massive amount of data from a wide spectrum of
energy-related sources, such as smart meters' data, sensors and other Internet of things …

Abstract Machine learning techniques have received a lot of interest in the exploration to
minimize the computational cost of computational fluid dynamics simulation. The present …

Wind energy has experienced rapid growth in the energy market over the last two decades,
and this growth would not have been possible without the development of wind turbines that …

Wake galloping is a phenomenon of aerodynamic instability and has vast potential in energy
harvesting. This paper investigates the vibration response of wake galloping piezoelectric …

Numerous studies have been carried out to measure wind pressures around circular
cylinders since the early 20th century due to its engineering significance. Consequently, a …

A robust machine learning methodology is used to generate a site-specific power-curve of a
full-scale isolated wind turbine operating in an atmospheric boundary layer to drastically …