A systematic review on the application of machine learning in exploiting mineralogical data in mining and mineral industry

M Jooshaki, A Nad, S Michaux - Minerals, 2021 - mdpi.com
Machine learning is a subcategory of artificial intelligence, which aims to make computers
capable of solving complex problems without being explicitly programmed. Availability of …

[HTML][HTML] A review of modeling and control strategies for cone crushers in the mineral processing and quarrying industries

AS Yamashita, A Thivierge, TAM Euzébio - Minerals Engineering, 2021 - Elsevier
Run-of-mine ore is usually too large to be useful for construction or metallurgy. Large
particles must be reduced to specific sizes to either comply with aggregate sizing …

Digitalization solutions in the mineral processing industry: the case of GTK Mintec, Finland

A Nad, M Jooshaki, E Tuominen, S Michaux, A Kirpala… - Minerals, 2022 - mdpi.com
The technologies used in mineral process engineering are evolving. The digital mineral
processing solutions are based on advances in our ability to instrumentally measure …

[PDF][PDF] A Systematic Review on the Application of Machine Learning in Exploiting Mineralogical Data in Mining and Mineral Industry. Minerals 2021, 11, 816

M Jooshaki, A Nad, S Michaux, U König, Y Choi - mdpi. com, 2021 - academia.edu
Machine learning is a subcategory of artificial intelligence, which aims to make computers
capable of solving complex problems without being explicitly programmed. Availability of …

Laser-induced breakdown spectroscopy and hyperspectral imaging data fusion for improved mineralogical analysis of copper concentrates

R Fuentes, D Luarte, C Sandoval, AK Myakalwar… - IFAC-PapersOnLine, 2022 - Elsevier
The mineralogical analyses of copper concentrates are very important not only for technical
reasons, to monitor and control the smelting processes, but also for commercial purposes …

[HTML][HTML] Mineral Potential Mapping Using Satellite Images of Sentinel-2, Landsat-8 and ASTER for Iron Ore at Esfordi 1: 100000 Sheet

F Ahmadi, H Aghajani, M Abedi - Journal of Mineral …, 2022 - jmre.journals.ikiu.ac.ir
The Esfordi 1: 100,000 geological sheet is situated at the Bafgh-Posht-e-Badam district in
the central Iran structural zone. Due to the high mineral potentials in this region, many …

[PDF][PDF] Digitalization Solutions in the Mineral Processing Industry: The Case of GTK Mintec, Finland. Minerals 2022, 12, 210

A Nad, M Jooshaki, E Tuominen, S Michaux, A Kirpala… - 2022 - academia.edu
The technologies used in mineral process engineering are evolving. The digital mineral
processing solutions are based on advances in our ability to instrumentally measure …