Classification problems and their corresponding solving approaches constitute one of the
fields of machine learning. The application of classification schemes in Renewable Energy …

This paper studies the different machine learning classification algorithms to predict the
COVID-19 recovered and deceased cases. The k-fold cross-validation resampling technique …

Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of
solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using …

Energy consumption classification is one of the most widely-used approaches in the energy
area that is applied in various applications such as household, commercial, urban, rural …

Aiming at the problem of unnecessary waste of power resources in the power system
caused by the uncertainty of wind farm output, and then affecting the economics of the …

This work explores the ability to dynamically group the Wind Turbine (WT) of a Wind Farm
(WF) based on the behavior of some of their Supervisory Control And Data Acquisition …

For the problem of simplifying pattern-based modeling procedures, an improved pattern-
based modeling method is put forward via pattern classification for a class of complex …

While the space of renewable energy forecasting has received significant attention in the
last decade, literature has primarily focused on machine learning models that train on only …

This paper studies the different machine learning classification algorithms to predict the
COVID-19 recovered and deceased cases. The k-fold cross-validation resampling technique …

In this work, we explore the ability to dynamically group the Wind Turbine (WT) of a Wind
Farm (WF) based on the behaviour of some of their Supervisory Control And Data …