In the world, wind power is rapidly becoming a generation technology of significance.
Unpredictability and variability of wind power generation is one of the fundamental …

Artificial intelligence (AI) techniques are becoming useful as alternate approaches to
conventional techniques or as components of integrated systems. They have been used to …

To maximize energy extraction, the nacelle of a wind turbine follows the wind direction.
Accurate prediction of wind direction is vital for yaw control. A tandem hybrid approach to …

Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …

As a type of clean and renewable energy source, wind power is widely used. However,
owing to the uncertainty of wind speed, it is essential to build an accurate forecasting model …

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 …

In this paper, a modified EMD-FNN model (empirical mode decomposition (EMD) based
feed-forward neural network (FNN) ensemble learning paradigm) is proposed for wind …

In this study, three models of machine learning algorithms are implemented to predict wind
speed, wind direction and output power of a wind turbine. The first model is multilayer feed …

Recently, wind speed forecasting as an effective computing technique plays an important
role in advancing industry informatics, while dealing with these issues of control and …

Abstract Machine learning algorithms (MLAs) are applied to predict wind speed data for
Osorio wind farm that is located in the south of Brazil, near the Osorio city. Forecasting wind …