I. M. Mujtaba

Empowering Wind Energy Output Optimization: Comparative Assessment of Hybrid Artificial Intelligence Models Towards Wind Speed Forecasting Accuracy

This study proposes a hybrid machine learning approach that combines the strengths of random forest regression, artificial neural network, and support vector regression as a meta-model for wind speed forecasting, and finds that temperature, relative humidity, and cyclical time-encoded features are the most important in...