Introducing a Hybrid Method for Estimating Wind Speed Using Information from Neighboring Stations in Isfahan Province

The prediction of wind components including wind speed is one of the important factors, especially in the case of evaporation in a watershed. In this paper, in order to increase the efficiency of support vector machines (SVM) for predicting wind speed, the SVM model was combined with the firefly optimization algorithm called hybrid model (HM). In this regard, the wind speed data from synoptic stations of Isfahan province were used to estimate the monthly wind speed values of the unknown neighboring stations. Then, the efficiency of the SVM and HM models was compared. Finally, the RMSE, MAE, WI, and NS indices were used to evaluate the both models performance efficiency.  The results in the evaluation step showed that the hybrid model (HM) with high correlation and lower error values has higher performance efficiency as compared to the SVM model. as Also, the method of using neighboring stations data as inputs for the predictive models of unknown station is a proper method for estimation of wind speed.