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2015 | 17 | 3 | 62-69
Tytuł artykułu

Statistical modeling of copper losses in the silicate slag of the sulfide concentrate smelting process

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This article presents the results of the statistical modeling of copper losses in the silicate slag of the sulfide concentrates smelting process. The aim of this study was to define the correlation dependence of the degree of copper losses in the silicate slag on the following parameters of technological processes: SiO2, FeO, Fe3O4, CaO and Al2O3 content in the slag and copper content in the matte. Multiple linear regression analysis (MLRA), artificial neural networks (ANNs) and adaptive network based fuzzy inference system (ANFIS) were used as tools for mathematical analysis of the indicated problem. The best correlation coefficient (R2 = 0.719) of the final model was obtained using the ANFIS modeling approach.
Słowa kluczowe
Wydawca

Rocznik
Tom
17
Numer
3
Strony
62-69
Opis fizyczny
Daty
wydano
2015-09-01
online
2015-09-19
Twórcy
  • University of Belgrade, Technical Faculty in Bor Vojske Jugoslavije 12, 19210 Bor, Serbia
  • University of Belgrade, Technical Faculty in Bor Vojske Jugoslavije 12, 19210 Bor, Serbia
  • University of Belgrade, Technical Faculty in Bor Vojske Jugoslavije 12, 19210 Bor, Serbia
Bibliografia
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  • 18. Živković, Ž., Mihajlović I. & Nikolić Đ. (2009). Artificial neural network method applied on the nonlinear multivariate problems. Serb. J. Manag., 4, 143–155.
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  • 33. Subashini, L. & Vasudeven M. (2012). Adaptive neuro-fuzzy inference system (ANFIS) – based models for predicting the weld bead width and depth of penetration from the infrared thermal image of the weld pool. Metall. Mater. Trans. B, 43, 145–154. DOI: 10.1007/s11663-011-9570-x.[Crossref][WoS]
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.-psjd-doi-10_1515_pjct-2015-0051
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