Assessing data mining algorithms to predict the quality of groundwater resources for determining irrigation hazard

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Detalles Bibliográficos
Publicado en:	Environmental Monitoring and Assessment vol. 195, no. 2 (Feb 2023), p. 319
Autor principal:	Masoudi, Reyhaneh
Otros Autores:	Mousavi, Seyed Roohollah, Rahimabadi, Pouyan Dehghan, Panahi, Mehdi, Rahmani, Asghar
Publicado:	Springer Nature B.V.
Materias:	Parameters Groundwater quality Groundwater resources Water sampling Groundwater irrigation Sodium Data mining Machine learning Irrigation Salinity Water resources Spatial distribution Groundwater Accuracy Algorithms Mathematical models Regression analysis Collinearity Environmental science Maps Hydrochemicals Data analysis Water analysis Statistical analysis Water quality Environmental monitoring Environmental
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