Wind Speed Prediction Using Machine Learning Algorithms
This study proposes a wind speed prediction model using machine learning algorithms, including random forest, support vector machine, and gradient boosting.
This study proposes a wind speed prediction model using machine learning algorithms, including random forest, support vector machine, and gradient boosting.
The National Renewable Energy Laboratory (NREL) uses machine learning to improve wind speed prediction, which is crucial for wind energy production.
This article reviews various machine learning and deep learning techniques for wind speed forecasting, including recurrent neural networks and long short-term memory networks.
This GitHub repository provides a wind speed prediction model using long short-term memory (LSTM) and gated recurrent unit (GRU) algorithms.
Forbes discusses how machine learning can improve wind speed prediction, which is essential for the wind energy industry.
This survey paper reviews various machine learning techniques used for wind speed prediction, including supervised, unsupervised, and reinforcement learning methods.
This online course on Coursera covers wind energy forecasting using machine learning and artificial intelligence techniques.
This journal article proposes a wind speed prediction model using machine learning and data mining techniques, including decision trees and clustering analysis.