Intelligent System for Reducing Waste and Enhancing Efficiency in Copper Production Using Machine Learning

Intelligent System for Reducing Waste and Enhancing Efficiency in Copper Production Using Machine Learning

The growing environmental impact of copper production necessitates innovative approaches for optimizing metallurgical processes and minimizing waste. This study addresses this challenge by leveraging advanced machine learning (ML) techniques to enhance the efficiency of pyrometallurgical operations...

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Bibliographic Details
Main Authors: Bagdaulet Kenzhaliyev, Timur Imankulov, Aksultan Mukhanbet, Sergey Kvyatkovskiy, Maral Dyussebekova, Nurdaulet Tasmurzayev
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Metals
Subjects:
copper production
pyrometallurgy
machine learning
sustainable metallurgy
predictive modeling
backward prediction
Online Access:https://www.mdpi.com/2075-4701/15/2/186
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