Evaluation of random forests and generalized regression neural networks for daily reference evapotranspiration modelling

Author:

Feng Yu,Cui Ningbo,Gong Daozhi,Zhang Qingwen,Zhao Lu

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference38 articles.

1. Extreme Learning Machines: a new approach for prediction of reference evapotranspiration;Abdullah;J. Hydrol.,2015

2. Crop Evapotranspiration. Guide Lines for Computing Crop Evapotranspiration. FAO Irrigation and Drainage Paper No. 56;Allen,1998

3. Hydrology and water resources;Amell,2001

4. Random forests;Breiman;Mach. Learn.,2001

5. Temporal-spatial distribution characteristics and causes analysis of reference crop evapotranspiration in hilly area of central Sichuan;Feng;Trans. Chin. Soc. Agric. Eng.,2014

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