Prediction of reference crop evapotranspiration: Empirical and machine learning approaches

Author:

Jayashree T.R.,Reddy N.V. Subba,Acharya U. Dinesh,Eslamian Saeid

Publisher

Elsevier

Reference52 articles.

1. Hybrid of artificial neural network-genetic algorithm for prediction of reference evapotranspiration (ETˆ sub 0ˆ) in arid and semiarid regions;Abdullah;J. Agric. Sci.,2014

2. Modification and validation of Priestley–Taylor model for estimating cotton evapotranspiration under plastic mulch condition;Ai;J. Hydrometeorol.,2016

3. Comparative analysis of reference evapotranspiration from the surface of rainfed grass in central Serbia, calculated by six empirical methods against the Penman-Monteith formula;Alexandris;Eur. Water,2008

4. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements;Allen,1998

5. Heuristic methods applied in reference evapotranspiration modeling;Althoff;Cienc. Agrotecnol.,2018

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