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Articles

Self-organizing maps for pseudo-lithological classification of 3D airborne electromagnetic, gravity gradiometry and magnetic inversions

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Pages 1-4 | Published online: 26 Feb 2019

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Adrián Misael León-Sánchez, Luis A. Gallardo & Alan Yusen Ley-Cooper. (2018) Two dimensional cross-gradient joint inversion of gravity and magnetic data sets constrained by airborne electromagnetic resistivity in the Capricorn Orogen, Western Australia. Exploration Geophysics 49:6, pages 940-951.
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Yulong Dong, Yang Liu, Wuxu Peng, Yansi Chen, Junjie Fan, Xiaobing Huang, Huilong Liu & Qiang Sun. (2023) 3D pseudo-lithologic modeling via iterative weighted k-means++ algorithm from Tengger Desert cover area, China. Frontiers in Earth Science 11.
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Z. Smillie, V. Demyanov, J. McKinley & M. Cooper. (2023) Unsupervised classification applications in enhancing lithological mapping and geological understanding: a case study from Northern Ireland. Journal of the Geological Society 180:4.
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Carmine Cutaneo, Andrea Vitale & Maurizio Fedi. (2023) Unsupervised boundary analysis of potential field data: A machine learning method. GEOPHYSICS 88:3, pages G57-G65.
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Zhiqiang Zhang, Gongwen Wang, Emmanuel John M. Carranza, Shuren Yang, Ke Zhao, Wangdong Yang & Deming Sha. (2021) Three-Dimensional Pseudo-Lithologic Modeling Via Adaptive Feature Weighted k-Means Algorithm from Multi-Source Geophysical Datasets, Qingchengzi Pb–Zn–Ag–Au District, China. Natural Resources Research 31:4, pages 2163-2179.
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Simo Piippo, Martiya Sadeghi, Emilia Koivisto, Pietari Skyttä & Tim Baker. (2022) Semi-automated geological mapping and target generation from geochemical and magnetic data in Halkidiki region, Greece. Ore Geology Reviews 142, pages 104714.
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Aline Melo & Yaoguo Li. (2021) Geology differentiation by applying unsupervised machine learning to multiple independent geophysical inversions. Geophysical Journal International 227:3, pages 2058-2078.
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Carmine Cutaneo, Andrea Vitale & Maurizio Fedi. (2021) Unsupervised boundary analysis of potential field data: A machine learning method. Unsupervised boundary analysis of potential field data: A machine learning method.
Aline Tavares Melo, Jiajia Sun & Yaoguo Li. (2017) Geophysical inversions applied to 3D geology characterization of an iron oxide copper-gold deposit in Brazil. GEOPHYSICS 82:5, pages K1-K13.
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Yaoguo Li & Jiajia Sun. (2016) Geology differentiation with uncertainty estimation using inverted magnetization directions. Geology differentiation with uncertainty estimation using inverted magnetization directions.
Aline Melo & Yaoguo Li. (2016) Geological characterization applying k-means clustering to 3D magnetic, gravity gradient, and DC resistivity inversions: A case study at an iron oxide copper gold (IOCG) deposit. Geological characterization applying k-means clustering to 3D magnetic, gravity gradient, and DC resistivity inversions: A case study at an iron oxide copper gold (IOCG) deposit.
Yaoguo LiJiajia Sun. (2016) 3D magnetization inversion using fuzzy c -means clustering with application to geology differentiation . GEOPHYSICS 81:5, pages J61-J78.
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Leonardo Feltrin. (2015) KNIME an Open Source Solution for Predictive Analytics in the Geosciences [Software and Data Sets]. IEEE Geoscience and Remote Sensing Magazine 3:4, pages 28-38.
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Richard Smith. (2013) Electromagnetic Induction Methods in Mining Geophysics from 2008 to 2012. Surveys in Geophysics 35:1, pages 123-156.
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