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Estimation of Evapotranspiration forms the basis for computation of irrigation requirement of crop, and also it is considered as one of the vital component of hydrological cycle. This study describes the conceptual outline and implementation to test the ability of an artificial neural network (ANN) for accurate estimation of reference evapotranspiration (ETo). There are many conventional methods like FAO modified Penman method, temperature-based and radiation-based empirical methods are used todoi:10.14419/ijet.v7i3.12.16438 fatcat:gcvbgifjezbbbljuj4ixegsfae