USABILITY OF ARTIFICIAL INTELLIGENCE METHODS FOR ESTIMATION OF MONTHLY EVAPORATION

Evaporation, one of the most important components of the hydrological cycle, is influenced by many factors. Evaporation is a meteorological parameter that is difficult to predict due to this complex structure. In this study, the amount of monthly evaporation was estimated using different input combinations formed by meteorological parameters belonging to Karaman station in Konya Closed Basin. For this purpose, Artificial Neural Networks (ANN), Support Vector Regression (SVR), Adaptive Network Based Fuzzy Inference System (ANFIS) methods are used. As a result, SVR has been more successful than other methods in monthly evaporation prediction