Our latest made, authored by the Geopyörä team members Thiago de Alemida and Marcos de Paiva Bueno has been presented at the INAC 24 in Brazil! The paper examines how artificial intelligence can enhance mineral processing by estimating ore hardness using data from nuclear analytical techniques like X-ray Diffraction (XRD) and Inductively Coupled Plasma Spectroscopy (ICP-AES). By applying machine learning, the study demonstrates a more efficient way to predict comminution parameters such as the DWI and BWI.
The findings show that AI models using ICP-AES data are capable of generating satisfactory data, being a great tool for estimating comminution parameters
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