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.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.