Bauxite quality classification by shrinkage methods

dc.authoridTutmez, Bulent/0000-0002-2618-3285
dc.authorwosidTutmez, Bulent/ABG-8630-2020
dc.contributor.authorTutmez, Bulent
dc.date.accessioned2024-08-04T20:44:34Z
dc.date.available2024-08-04T20:44:34Z
dc.date.issued2018
dc.departmentİnönü Üniversitesien_US
dc.description.abstractGeochemically, bauxite ore may contain some clay minerals, aluminum oxides-hydroxides, and insoluble materials such as quartz and magnetite. The amounts of the geochemical components and their ratios (modules) have critical importance in bauxite quality classification. A classification study was conducted by way of Al2O3/ SiO2 module and its corresponding indicators such as spatial coordinates, thickness, and some of the geochemical contributors. The classification was made benefit of two advanced regularization methods such as ridge and the Lasso regression methods. Accuracy, interpretability and simplicity were appraised. Both the algorithms had influence on reducing variance. The smoothing levels of the algorithms also were discussed. The resulting classification provided by the strong estimators can provide a reliable tool for industrial decision making and control.en_US
dc.identifier.doi10.1016/j.gexplo.2018.05.002
dc.identifier.endpage27en_US
dc.identifier.issn0375-6742
dc.identifier.issn1879-1689
dc.identifier.scopus2-s2.0-85048068626en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage22en_US
dc.identifier.urihttps://doi.org/10.1016/j.gexplo.2018.05.002
dc.identifier.urihttps://hdl.handle.net/11616/98320
dc.identifier.volume191en_US
dc.identifier.wosWOS:000436826000002en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofJournal of Geochemical Explorationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBauxiteen_US
dc.subjectChemically-based classificationen_US
dc.subjectShrinkageen_US
dc.subjectRidge regressionen_US
dc.subjectThe Lassoen_US
dc.titleBauxite quality classification by shrinkage methodsen_US
dc.typeArticleen_US

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