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 …

The harmful consequences of fossil fuels use has resulted in the promotion of clean and
renewable energies. During the past decades, green technologies have experienced a …

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 …

It is of vital importance to use proper training data to perform accurate shortterm load
forecasting (STLF) based on artificial neural networks. The pattern of the loads which are …

With the development of China's electricity market reform, electricity transaction is still the
main form of mid-and long-term market transaction. Reasonable long-term electricity …

현재 급격한 화석 에너지의 사용 증가로 인해 자원이 고갈되고 있으며, 심각한 환경오염의
문제가 발생하고 있다. 이러한 화석 에너지의 문제점 때문에 무공해이면서 자원 량이 무한에 …