Deep learning and its application in geochemical map**

R Zuo, Y ** using machine learning methods: A case study from Tongling ore district, eastern China
T Sun, F Chen, L Zhong, W Liu, Y Wang - Ore Geology Reviews, 2019‏ - Elsevier
Predictive modelling of mineral prospectivity using GIS is a valid and progressively more
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …

Genetic algorithm to optimize the SVM and K-means algorithms for map** of mineral prospectivity

R Ghezelbash, A Maghsoudi, M Shamekhi… - Neural Computing and …, 2023‏ - Springer
Unsupervised clustering (eg, K-means) and supervised machine learning [eg, support vector
machines (SVMs)] methods can be used in data-driven classification and predictive …

Lithospheric architecture of the Lhasa terrane and its control on ore deposits in the Himalayan-Tibetan orogen

Z Hou, L Duan, Y Lu, Y Zheng, D Zhu… - Economic …, 2015‏ - pubs.geoscienceworld.org
Magmatic-hydrothermal ore deposits in collisional orogens are new targets for modern
mineral exploration, yet it is unclear why they preferentially occur in some specific tectonic …

Data analysis methods for prospectivity modelling as applied to mineral exploration targeting: State-of-the-art and outlook

M Yousefi, EJM Carranza, OP Kreuzer… - Journal of Geochemical …, 2021‏ - Elsevier
Mineral exploration targeting is a highly complex decision-making task. Two key risk factors,
the quality of exploration data and robustness of the underlying conceptual targeting model …

[HTML][HTML] Ensemble learning models with a Bayesian optimization algorithm for mineral prospectivity map**

J Yin, N Li - Ore geology reviews, 2022‏ - Elsevier
Abstract Machine learning algorithms have been widely applied in mineral prospectivity
map** (MPM). In this study, we implemented ensemble learning of extreme gradient …

Exploration information systems–A proposal for the future use of GIS in mineral exploration targeting

M Yousefi, OP Kreuzer, V Nykänen, JMA Hronsky - Ore Geology Reviews, 2019‏ - Elsevier
The advent of modern data collection and storage technologies has brought about a huge
increase in data volumes with both traditional and machine learning tools struggling to …

Global distribution of sediment-hosted metals controlled by craton edge stability

MJ Hoggard, K Czarnota, FD Richards, DL Huston… - Nature …, 2020‏ - nature.com
Sustainable development and the transition to a clean-energy economy drives ever-
increasing demand for base metals, substantially outstrip** the discovery rate of new …

Translation of the function of hydrothermal mineralization-related focused fluid flux into a mappable exploration criterion for mineral exploration targeting

M Yousefi, JMA Hronsky - Applied Geochemistry, 2023‏ - Elsevier
Formation of hydrothermal mineralization is related to the late stages of, or immediate
following, orogenic compressional regimes that have been superimposed on arc …