GEOLOGICAL MAPPING USING MACHINE LEARNING ALGORITHMS

12 citations as recorded by crossref.

1. Unsupervised classification applications in enhancing lithological mapping and geological understanding: a case study from Northern Ireland Z. Smillie et al. https://doi.org/10.1144/jgs2022-136
2. Comparison of Machine Learning Methods and Ordinary Kriging for Gravimetric Mapping: Application to Yagoua Area (Northern Cameroon) M. Luther et al. https://doi.org/10.1155/je/6613167
3. A comparative analysis of multi-index overlay and fuzzy ordered weighted averaging methods for porphyry Cu prospectivity mapping using remote sensing data: the case study of Chahargonbad area, SE of Iran S. Riahi et al. https://doi.org/10.1080/10106049.2022.2159068
4. Geological characterization and machine learning-based mapping of the Nkout iron deposit, South Cameroon A. Boroh et al. https://doi.org/10.1007/s44288-025-00376-3
5. A review of machine learning in processing remote sensing data for mineral exploration H. Shirmard et al. https://doi.org/10.1016/j.rse.2021.112750
6. Machine Learning-Based Mineral Quantification from Lower Cambrian Shale in the Sichuan Basin: Implications for Reservoir Quality X. Ye et al. https://doi.org/10.3390/min15030286
7. Predictive modeling of geophysical anomalies in the metasediments of Bugaji area, part of Malumfashi Schist Belt, North-Western Nigeria A. Ali & M. Muhammad https://doi.org/10.1016/j.ees.2025.07.005
8. UTILIZAÇÃO DE MACHINE LEARNING PARA GERAÇÃO DE MAPAS GEOLÓGICOS PREDITIVOS DE CURTO PRAZO V. Soares & S. Arcanjo https://doi.org/10.56083/RCV5N11-121
9. Recent advances in the use of public domain satellite imagery for mineral exploration: A review of Landsat-8 and Sentinel-2 applications Z. Adiri et al. https://doi.org/10.1016/j.oregeorev.2020.103332
10. Comparison of deep learning models for 1D magnetotelluric inversion H. Saibi et al. https://doi.org/10.1016/j.acags.2026.100320
11. The contribution of pattern recognition techniques in geomorphology and geology: the case study of Tinos Island (Cyclades, Aegean, Greece) E. Toulia et al. https://doi.org/10.1080/22797254.2017.1405716
12. A Systematic Review on the Application of Machine Learning in Exploiting Mineralogical Data in Mining and Mineral Industry M. Jooshaki et al. https://doi.org/10.3390/min11080816