This study has developed a novel methodology for predicting groundwater quality for irrigation use in the study area based on machine learning algorithms and ...
The current research objective is to estimate the irrigation water quality indices in the Nand Samand catchment by developing machine learning models.
Apr 11, 2023 · The result indicated that the M5P model has the potential to predict the water quality indices even under limited input parameters scenarios in ...
Apr 1, 2023 · Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices. Dimple a,*, Pradeep Kumar ...
Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices ; Journal: Ecological Informatics, 2023, p.
This study aims to evaluate the performance of four ensemble machine learning methods, ie, Random Committee, Discretization Regression, Reduced Error Pruning ...
Missing: driven | Show results with:driven
Mar 21, 2022 · Multiple linear regression is regarded as a reliable approach for assessing groundwater quality since it creates a minimal dataset of indicators ...
Missing: discretization | Show results with:discretization
Currently, there is a need for more automated methods for evaluating and monitoring water quality for irrigation purposes, considering different aspects, from ...
Missing: Combination discretization
Mar 21, 2022 · Multiple linear regression is regarded as a reliable approach for assessing groundwater quality since it creates a minimal dataset of indicators ...
Prediction of irrigation water quality indices based on machine learning ...
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The objective of this work was to predict the irrigation water quality index of the Bahr El-Baqr, Egypt, based on non-expensive approaches that requires simple ...
Missing: discretization | Show results with:discretization