Amel Ali Alhussan1, El-Sayed M. El-kenawy2,3, Hussah Nasser AlEisa1,*, M. El-SAID4,5, Sayed A. Ward6,7, Doaa Sami Khafaga1
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2619-2635, 2022, DOI:10.32604/cmc.2022.030445
Abstract Effective technology for wind direction forecasting can be realized using the recent advances in machine learning. Consequently, the stability and safety of power systems are expected to be significantly improved. However, the unstable and unpredictable qualities of the wind predict the wind direction a challenging problem. This paper proposes a practical forecasting approach based on the weighted ensemble of machine learning models. This weighted ensemble is optimized using a whale optimization algorithm guided by particle swarm optimization (PSO-Guided WOA). The proposed optimized weighted ensemble predicts the wind direction given a set of input features. The conducted experiments employed the wind… More >
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