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Title: Recursive feature elimination and neural networks applied to the forecast of mass and metallurgical recoveries in a brazilian phosphate mine
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dc.contributor.authorNiquini, Fernanda Gontijo Fernandes
dc.contributor.authorBranches, André Miranda Brito
dc.contributor.authorCosta, João Felipe Coimbra Leite
dc.contributor.authorMoreira, Gabriel de Castro
dc.contributor.authorSchneider, Claudio Luiz
dc.contributor.authorAraújo, Florence Cristiane de
dc.contributor.authorCapponi, Luciano Nunes
dc.date.accessioned2023-06-12T17:39:49Z
dc.date.available2023-06-12T17:39:49Z
dc.date.issued2023
dc.identifier.urihttps://doi.org/10.3390/min13060748
dc.language.isoen_US
dc.publisherMinerals, v.13, 2023.
dc.subjectGeometalurgia
dc.subjectFosfato
dc.subjectRedes neurais
dc.subjectSeleção de recursos
dc.subjectGeometallurgy
dc.subjectNeural networks
dc.subjectPhosphate
dc.subjectFeature selection
dc.titleRecursive feature elimination and neural networks applied to the forecast of mass and metallurgical recoveries in a brazilian phosphate mine
dc.typeArticle
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