Abstract
The appropriate planning and management of irrigated agriculture require accurate assessment of the ET0. To estimate the reference evapotranspiration (ET0), soft computing techniques are used. Based on the climatological data collected from the IARI regional station at Pusa for the period from 1981 to 2016, the conventional methods of Hargreaves method and FAO 56 Penman method were used to determine ET0. In order to estimate ET0, three soft computing techniques were used, i.e. support vector machine (SVM), Gaussian process regression (GPR) and artificial neural network (ANN). The reliability of these computational methods was analysed based on the coefficient of determination. In comparison to SVM and GPR computational approaches, the final result shows that ANN is the best methodology for prediction of ET0.
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Roy, L.B., Praveen, K. (2022). Study of ET0 by Using Soft Computing Techniques in the Eastern Gandak Project in Bihar, India—A Case Study. In: Kumar, R., Ahn, C.W., Sharma, T.K., Verma, O.P., Agarwal, A. (eds) Soft Computing: Theories and Applications. Lecture Notes in Networks and Systems, vol 425. Springer, Singapore. https://doi.org/10.1007/978-981-19-0707-4_47
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