[HTML][HTML] Principal components analysis and K-means clustering of till geochemical data: Mapping and targeting of prospective areas for lithium exploration in …
M Sadeghi, P Casey, EJM Carranza, EP Lynch - Ore Geology Reviews, 2024 - Elsevier
To achieve the demand for elements used for the green transition energy, such as lithium, it
is necessary to recognize the spatial distribution of the concentrations of these elements in …
is necessary to recognize the spatial distribution of the concentrations of these elements in …
How do non-deposit sites influence the performance of machine learning-based gold prospectivity mapping? A study case in the Pitangui Greenstone Belt, Brazil
BOL Ribeiro, D Barbuena, GHC de Melo… - Journal of Geochemical …, 2024 - Elsevier
One of the greatest challenges in mineral prospectivity mapping (MPM) research nowadays
is to find a solid methodology that ensures the reliability of the prospectivity model during the …
is to find a solid methodology that ensures the reliability of the prospectivity model during the …
Machine learning models to predict rare earth elements distribution in Tethyan phosphate ore deposits: Geochemical and depositional environment implications
N Tahar-Belkacem, O Ameur-Zaimeche, R Kechiched… - Geochemistry, 2024 - Elsevier
The global market for rare earth elements (REE) is growing rapidly, driven by rising demand
and limited production sources, prompting interest in recovering REE from secondary …
and limited production sources, prompting interest in recovering REE from secondary …
Modelagem prospectiva dos depósitos auríferos do Greenstone Belt Pitangui (MG) integrando dados geológicos, geofísicos e geoquímicos
BOL Ribeiro - 2022 - acervo.ufvjm.edu.br
Atualmente, a exploração mineral tem se dedicado fortemente à elaboração de mapas de
prospectividade mineral. Estes mapas são uma poderosa ferramenta em estudos regionais …
prospectividade mineral. Estes mapas são uma poderosa ferramenta em estudos regionais …