Prediction of results of floatation process using artificial neural networks
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Date
2025
Authors
Trumić, Maja
Balanović, Katarina
Gavrilović, Tamara
Journal Title
Journal ISSN
Volume Title
Publisher
University of Belgrade, Technical Faculty in Bor
Source
Proceedings - XVI International Mineral Processing and Recycling Conference, IMPRC, 28 – 30 May 2025, Belgrade, Serbia
Volume
Issue
Abstract
In 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.
Description
Keywords
Artificial neural networks, Machine learning, Flotation, Deinking
Citation
DOI
10.5937/IMPRC25659T
Scopus
ISSN
ISBN
978-86-6305-158-4
License
CC-BY-NC-ND