Prediction of results of floatation process using artificial neural networks

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dc.citation.epage664
dc.citation.rankM33
dc.citation.spage659
dc.contributor.authorTrumić, Maja
dc.contributor.authorBalanović, Katarina
dc.contributor.authorGavrilović, Tamara
dc.date.accessioned2025-12-12T12:29:07Z
dc.date.available2025-12-12T12:29:07Z
dc.date.issued2025
dc.description.abstractIn this paper, the use of artificial neural networks in the flotation process is presented and analyzed. Apart from utilization of flotation in the mineral processing, deinking flotation is used for separation of ink particles from the cellulose fibers. The time of deinking flotation, pH value, reagents such as oleic acid, oleic acid with CaCl2, oleic acid with AlCl2 as well as concentration of reagents were used as input for the network. The recovery of toner particles in froth was used as output data for the network. The neural network demonstrated high correlation coefficients during training (0.97), validation (0.96), and testing (0.94), and subsequent accuracy testing confirmed these results.
dc.identifier.doi10.5937/IMPRC25659T
dc.identifier.isbn978-86-6305-158-4
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/6054
dc.language.isoen
dc.publisherUniversity of Belgrade, Technical Faculty in Bor
dc.rights.licenseCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceProceedings - XVI International Mineral Processing and Recycling Conference, IMPRC, 28 – 30 May 2025, Belgrade, Serbia
dc.subjectArtificial neural networks
dc.subjectMachine learning
dc.subjectFlotation
dc.subjectDeinking
dc.titlePrediction of results of floatation process using artificial neural networks
dc.typeconferenceObject
dc.type.versionpublishedVersion

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