To cope with the stochastic wind nature, it is essential to harvest the maximum power by the
wind energy conversion system (WECS). Therefore, this article presents an overview of the …

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 …

Nowadays, learning-based modeling system is adopted to establish an accurate prediction
model for renewable energy resources. Computational Intelligence (CI) methods have …

The wind speed forecasting plays an important role in the planning, controlling and
monitoring of the intelligent wind power systems. Since the wind speed signal is stochastic …

This paper proposes a new hybrid stochastic training algorithm using the recently proposed
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …

Wind power is the most reliable and developed renewable energy source over past
decades. With the rapid penetration of the wind generators in the power system grid, it is …

Condition monitoring in wind turbines aims at detecting incipient faults at an early stage to
improve maintenance. Artificial neural networks are a tool from machine learning that is …

Renewable energy is being embraced globally as a viable alternative to conventional fossil
fuels generators. This is in direct response to the challenge of depleting fossil fuel reserves …

Artificial neural networks (ANNs) have been widely applied for the prediction of dye
adsorption during the last decade. In this paper, the applications of ANN methods, namely …

Daily solar radiation is an important variable in many models. In this paper, the accuracy and
performance of three soft computing techniques (ie, adaptive neuro-fuzzy inference system …