Algorithm and Model of Intelligent Classification for Optimizing the Parameters of Beneficiation Technology

Andrey Kupin, Dmytro Zubov, Yuriy Osadchuk, Vadym Saiapin

2022

Abstract

Based on the application of the classification control approach, a generalized algorithm for optimization of beneficiation processes is proposed. The results of computer modelling of the classification optimization process on the example of real indicators of magnetite quartzite beneficiation are presented. The results of classification and evolutionary optimization procedures are compared. It was concluded that the proposed intelligent classification method is able to determine the vector of settings and predict the TP beneficiation with satisfactory accuracy. It is confirmed that the developed algorithms and control principles can be applied to determine the required parameter values in modern ICS.

Paper Citation

in Harvard Style

Kupin A., Zubov D., Osadchuk Y. and Saiapin V. (2022). Algorithm and Model of Intelligent Classification for Optimizing the Parameters of Beneficiation Technology. In Proceedings of the 5th Workshop for Young Scientists in Computer Science and Software Engineering - Volume 1: CS&SE@SW; ISBN 978-989-758-653-8, SciTePress, pages 5-12. DOI: 10.5220/0012008800003561

in Bibtex Style

@conference{cs&se@sw22,
author={Andrey Kupin and Dmytro Zubov and Yuriy Osadchuk and Vadym Saiapin},
title={Algorithm and Model of Intelligent Classification for Optimizing the Parameters of Beneficiation Technology},
booktitle={Proceedings of the 5th Workshop for Young Scientists in Computer Science and Software Engineering - Volume 1: CS&SE@SW},
year={2022},
pages={5-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012008800003561},
isbn={978-989-758-653-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th Workshop for Young Scientists in Computer Science and Software Engineering - Volume 1: CS&SE@SW
TI - Algorithm and Model of Intelligent Classification for Optimizing the Parameters of Beneficiation Technology
SN - 978-989-758-653-8
AU - Kupin A.
AU - Zubov D.
AU - Osadchuk Y.
AU - Saiapin V.
PY - 2022
SP - 5
EP - 12
DO - 10.5220/0012008800003561
PB - SciTePress