A novel ensemble wind speed forecasting method using the differential weighting scheme and principal component analysis

Wind speed forecasting has found economic significance as it can increase operational efficiency. In this regard, an accurate forecast of wind is crucial in the application resources. This study intended to incorporate independent and output variables input support vector regression (SVR) Zanjan Ahvaz stations Iran. The were minimum, maximum, mean temperatures, relative humidity, precipitation, average visibility, dew point temperature. incorporation conducted with principal component analysis (PCA) differential weighting scheme (DWS), respectively. DWS combined forecasts linear regression, SVR, group method data handling (GMDH) which SVR showed best outperformed other three mentioned models. PCA (DWS-PCA) improved capability DWS-PCA a novel was significant terms stability. be robust approach for some subjects such renewable energy, meteorological decisions.