Abstract
In this study, the monthly mean daily global solar radiation (GSR) is modeled by artificial neural network (ANN), multilinear regression analysis (MLRA), and adaptive network-based fuzzy inference system (ANFIS) methods in the eight cities of Turkey. The results of three different models are compared and evaluated for these cities. The monthly means of daily sunshine duration, air temperature, relative humidity, wind speed, soil temperature, and GSR data of the cities are obtained from General Directorate of Meteorology and used to develop the models. Seven input parameters are determined using these meteorological data and some geographical equations. The root mean square error (RMSE), the mean absolute percentage error (MAPE), and the correlation coefficient (R) indicators are used to evaluate the performance of the models. For these performance indicators, the best values are obtained with ANN models.
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