Machine Learning-Based Mapping for Mineral Exploration.
- Published in:
- Mathematical Geosciences, 2023, v. 55, n. 7, p. 891, doi. 10.1007/s11004-023-10097-3
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- Article
Works matching IS 18748961 AND DT 2023 AND VI 55 AND IP 7
Results: 7
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Projection Pursuit Random Forest for Mineral Prospectivity Mapping.
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- Mathematical Geosciences, 2023, v. 55, n. 7, p. 963, doi. 10.1007/s11004-023-10070-0
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- Publication type:
- Article
3
Bayesian Decomposition Modelling: An Interpretable Nonlinear Approach for Mineral Prospectivity Mapping.
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- Mathematical Geosciences, 2023, v. 55, n. 7, p. 897, doi. 10.1007/s11004-023-10067-9
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- Article
4
Supervised Mineral Prospectivity Mapping via Class-Balanced Focal Loss Function on Imbalanced Geoscience Datasets.
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- Mathematical Geosciences, 2023, v. 55, n. 7, p. 989, doi. 10.1007/s11004-023-10065-x
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- Article
5
The Anomaly Detector, Semi-supervised Classifier, and Supervised Classifier Based on K-Nearest Neighbors in Geochemical Anomaly Detection: A Comparative Study.
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- Mathematical Geosciences, 2023, v. 55, n. 7, p. 1011, doi. 10.1007/s11004-022-10042-w
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- Article
6
Improving Mineral Prospectivity Model Generalization: An Example from Orogenic Gold Mineralization of the Sturgeon Lake Transect, Ontario, Canada.
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- Mathematical Geosciences, 2023, v. 55, n. 7, p. 943, doi. 10.1007/s11004-022-10038-6
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- Publication type:
- Article
7
Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data.
- Published in:
- Mathematical Geosciences, 2023, v. 55, n. 7, p. 1035, doi. 10.1007/s11004-022-10023-z
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- Publication type:
- Article