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Adaptive Evapotranspiration Estimation under Sparse Meteorological Sensor Availability via Bayesian Calibration of the FAO-56 Penman–Monteith Equation and Masked Neural Network Modeling
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Outgoing claims: the papers this work cites, builds on, or argues with.
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An interpretable machine learning approach based on DNN, SVR, Extra Tree, and XGBoost models for predicting daily pan evaporation
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Intelligent optimization of Reference Evapotranspiration (ETo) for precision irrigation
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Enhancing irrigation water management based on ETo prediction using machine learning to mitigate climate change
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Machine Learning Based Prediction of Reference Evapotranspiration (ET 0 ) Using IoT
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Local and global sensitivity analysis and its contributing factors in reference crop evapotranspiration
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Precision Irrigation Management Using Machine Learning and Digital Farming Solutions
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Comparative Evaluation of Crop Evapotranspiration Estimation Methods in a Semi-Arid Region
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Advanced Monitoring and Management Systems for Improving Sustainability in Precision Irrigation
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Improvement of Hargreaves–Samani Reference Evapotranspiration Estimates in the Peruvian Altiplano
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Artificial Neural Network for Forecasting Reference Evapotranspiration in Semi-Arid Bioclimatic Regions
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