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

Abstract

This article presents the results of the statistical modeling of copper losses in the silicate slag of the sulfi de concentrates smelting process. The aim of this study was to defi ne 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), artifi cial 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 coeffi cient (R2 = 0.719) of the fi nal model was obtained using the ANFIS modeling approach.