Estimating Daily Pan Evaporation Data using Adaptive Neuro Fuzzy Inference System: Case Study within Van Local Station-Turkey

The aim of this study is to model the evaporation data, which one important parameters hydrological cycle, by using Adaptive Neuro Fuzzy Inference System (ANFIS). Four different models were designed starting from input up four inputs used average daily temperature (ºC), relative humidity (%), current pressure (hPa) and wind speed (m/s) as parameters. Total pan (mm) was selected output parameter. normalized data Van Local Station between 2013 - 2017 for training model. Data 2018 testing purposes. Also, two stations in cities comparison order determine whether prepared can be other stations. For purpose, a station Konya province with climatic characteristics similar Kocaeli selected. In all models, results observed, while observed relatively low compared previous comparison. fourth model, parameters, achieved lowest error values at got best R2 value