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In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation. The predictions are conducted on both daily and monthly mean scales for an Iranian coastal city. The proposed SVM–WT method is compared against other existing techniques to demonstrate its efficiency and viability. Three different sets of parameters are served as inputs to establish three models. The results indicate that the model using relative sunshine duration, difference between air temperatures, relative humidity, average temperature and extraterrestrial solar radiation as inputs shows higher performance than other models. The statistical analysis demonstrates that SVM–WT approach enjoys very good performance and outperforms other approaches. For the best SVM–WT model, the obtained statistical indicators of mean …