The largest obstacle that suppresses the increase of wind power penetration within the
power grid is uncertainties and fluctuations in wind speeds. Therefore, accurate wind power …

Wind energy has become one of the most important forms of renewable energy. Wind
energy conversion systems are more sophisticated and new approaches are required based …

Accurate wind power forecast is critical to the efficient and safe running of power systems. A
hybrid model that combines complementary ensemble empirical mode decomposition …

The use of renewable energy resources, especially wind power, is receiving strong attention
from governments and private institutions, since it is considered one of the best and most …

This study introduces a power forecasting model, the convolutional neural network (CNN)–
long short-term memory (LSTM)–attention mechanism (AM) algorithm (CNN–LSTM–AM) …

Abstract Warm Mix Asphalts (WMAs) are asphalt concretes produced at lower temperatures
than traditional Hot Mix Asphalts (HMAs). Nonetheless, the above is not enough to diminish …

For the wind speed prediction, many researchers have established prediction models based
on machine learning methods, statistical methods, and theoretical methods, that is, direct …

One of the conditions of submission of a paper for publication is that authors declare
explicitly that their work is original and has not been submitted to nor appeared in another …

Over the past few years, significant progress has been made in wind power generation
worldwide. Because of the turbulent nature of wind velocity, the management of wind …

This paper presents a 5-input artificial neural network (ANN) model for the prediction of the
thermal conductivity ratio of nanofluids to the base fluid (k nf/kf) of various nanofluids based …