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Found 4 papers, 0 papers with code
Integrating machine learning paradigms and mixed-integer model predictive control for irrigation scheduling
The results demonstrate the superiority of the proposed scheduler compared to a traditional irrigation scheduling method in terms of water use efficiency and crop yield improvement for both growing seasons.
Maximizing soil moisture estimation accuracy through simultaneous hydraulic parameter estimation using microwave remote sensing: Methodology and application
Improving the accuracy of soil moisture estimation is desirable from the perspectives of irrigation management and water conservation.
LSTM-based model predictive control with discrete inputs for irrigation scheduling
The development of well-devised irrigation scheduling methods is desirable from the perspectives of plant quality and water conservation.
Soil moisture map construction using microwave remote sensors and sequential data assimilation
Secondly, measurements obtained from the microwave sensors are assimilated into the field model using the extended Kalman filter to form an information fusion system, which will provide frequent soil moisture estimates and predictions in the form of moisture content maps.
