Simple fuzzy models for prediction of flotation indices

Simple item page
dc.citation.epage409
dc.citation.rankM33
dc.citation.spage404
dc.contributor.authorJovanović, Ivana
dc.contributor.authorConić, Vesna
dc.contributor.authorSokolović, Jovica
dc.contributor.authorKržanović, Daniel
dc.contributor.authorRadulović, Dragan
dc.date.accessioned2024-01-23T09:14:26Z
dc.date.available2024-01-23T09:14:26Z
dc.date.issued2023
dc.description.abstractThis paper presents the development and validation of two simple copper flotation models based on fuzzy logic (Mamdani and Takagi-Sugeno fuzzy inference system). Given that the Cu flotation process contains a large number of variables (especially inputs), models are called simple, because they contain only three input and three output variables. Input variables are feed grade, collector consumption in the roughing stage and overall frother consumption. Output variables are final concentrate grade and recovery as well as final tailings grade. The training and evaluation of the proposed models were accomplished on the basis of real process data from the industrial flotation plant of “Veliki Krivelj Mine”. The results showed that the proposed fuzzy models well describe the behavior of the industrial flotation plant in a wide range of circumstances (correlation coefficient R > 0.89 in all cases). There is almost no difference between the results, whether Mamdani and Takagi Sugeno fuzzy inference system is applied.
dc.identifier.isbn978-86-6305-133-1
dc.identifier.urihttps://imprc.tfbor.bg.ac.rs/download/IMPRC_2023_Proceedings.pdf
dc.identifier.urihttps://repozitorijum.tfbor.bg.ac.rs/handle/123456789/5808
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 - XV International Mineral Processing and Recycling Conference, IMPRC, 17-19 May 2023, Belgrade, Serbia, 2023, 404-409
dc.subjectFuzzy model
dc.subjectFlotation
dc.subjectCopper ore
dc.titleSimple fuzzy models for prediction of flotation indices
dc.typeconferenceObject
dc.type.versionpublishedVersion

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
IMPRC_2023_Proceedings-419-424full.pdf
Size:
2.52 MB
Format:
Adobe Portable Document Format
Download

Collections

NIR