Predicting of daily reference evapotranspiration via Adaptive Neuro-Fuzzy Inference System( ANFIS)

The estimation of evapotranspiration from vegetated surfaces balances and to estimate water availability and requirements. Reference evapotranspiration( ET,) just reflects weather conditions. Adaptive Neuro-Fuzzy Inference System(ANFIS), has the capacity of non-linear mapping between input layer and output layer by fuzzy inference, and has store and learn ability with the information of the neural network at the same time. In this paper, the computation of daily ET, by ANFIS is presented, comparing the results with the ET, calculated through FAO Penman-Monteith method in same period. Sunlight hour and maximum air temperature are as input variables in ANFIS according of regression analysis between every weather factors. The ANFIS for ET, estimator is built from training data, whose array list includes 1827 data of five years. The result of testing data, 213 data, to estimate ET, using this ANFIS, is acceptable comparing with the result of Penman-Monteith method.