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Abstract
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This paper presents the application of fuzzy concepts in the field of crop yield forecasting. In this regard, classical and fuzzy, using symmetric and non-symmetric triangular fuzzy number coefficients; regression models for wheat and oil seeds yield forecasting were used in Zanjan, West and East Azarbaijan Provinces (1984/2013). The predominance of various climatological parameters was determined using maximum correlation coefficient between climatological parameters and crop yield. The sensitivity analysis of climatological parameters indicated the diversity of climatological parameters in different Provinces. RRMSE criteria decreased 37.76% in symmetric fuzzy regression compare to classical and 15.6% in non-symmetric fuzzy compare to symmetric fuzzy regression. Based on error criteria, fuzzy regression has better performance in relation to the classical regression. There were not major differences between the performance of symmetric and non-symmetric fuzzy regression.
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