Coupling Process-Based Models and Machine Learning Algorithms for Predicting Yield and Evapotranspiration of Maize in Arid Environments

Coupling Process-Based Models and Machine Learning Algorithms for Predicting Yield and Evapotranspiration of Maize in Arid Environments

Crop yield prediction is critical for investigating the yield gap and potential adaptations to environmental and management factors in arid regions. Crop models (CMs) are powerful tools for predicting yield and water use, but they still have some limitations and uncertainties; therefore, combining t...

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Bibliographic Details
Main Authors: Ahmed Attia, Ajit Govind, Asad Sarwar Qureshi, Til Feike, Mosa Sayed Rizk, Mahmoud M. A. Shabana, Ahmed M.S. Kheir
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Water
Subjects:
DSSAT models
random forest
XGBoost
super learner
lasso regression
hyperparameters tuning
Online Access:https://www.mdpi.com/2073-4441/14/22/3647

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