Deep GMDH Neural Networks for Predictive Mapping of Mineral Prospectivity in Terrains Hosting Few but Large Mineral Deposits

Natural Resources Research ◽

10.1007/s11053-021-09984-5 ◽

2021 ◽

Author(s):

Mohammad Parsa ◽

Emmanuel John M. Carranza ◽

Bahman Ahmadi

Keyword(s):

Neural Networks ◽

Mineral Deposits ◽

Predictive Mapping ◽

Mineral Prospectivity

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A new strategy for spatial predictive mapping of mineral prospectivity: Automated hyperparameter tuning of random forest approach

Computers & Geosciences ◽

10.1016/j.cageo.2021.104688 ◽

2021 ◽

Vol 148 ◽

pp. 104688

Author(s):

Mehrdad Daviran ◽

Abbas Maghsoudi ◽

Reza Ghezelbash ◽

Biswajeet Pradhan

Keyword(s):

Random Forest ◽

Predictive Mapping ◽

New Strategy ◽

Mineral Prospectivity

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Artificial neural networks: A new method for mineral prospectivity mapping

Australian Journal of Earth Sciences ◽

10.1046/j.1440-0952.2000.00807.x ◽

2000 ◽

Vol 47 (4) ◽

pp. 757-770 ◽

Cited By ~ 139

Author(s):

W. M. Brown ◽

T. D. Gedeon ◽

D. I. Groves ◽

R. G. Barnes

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

New Method ◽

Mineral Prospectivity Mapping ◽

Artificial Neural ◽

Mineral Prospectivity ◽

Prospectivity Mapping

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MODELING THE SPATIAL DISTRIBUTION OF MINERAL DEPOSITS USING NEURAL NETWORKS

Natural Resource Modeling ◽

10.1111/j.1939-7445.2007.tb00215.x ◽

2008 ◽

Vol 20 (3) ◽

pp. 435-450 ◽

Cited By ~ 14

Author(s):

ANDREW SKABAR

Keyword(s):

Neural Networks ◽

Spatial Distribution ◽

Mineral Deposits

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Single-class classifier learning using neural networks: an application to the prediction of mineral deposits

Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693) ◽

10.1109/icmlc.2003.1259857 ◽

2004 ◽

Cited By ~ 7

Author(s):

A. Skabar

Keyword(s):

Neural Networks ◽

Mineral Deposits ◽

Single Class ◽

Classifier Learning

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Comparing the Performance of Different Neural Networks Architectures for the Prediction of Mineral Prospectivity

2005 International Conference on Machine Learning and Cybernetics ◽

10.1109/icmlc.2005.1526979 ◽

2005 ◽

Cited By ~ 6

Author(s):

Chun Che Fung ◽

Iyer ◽

Brown ◽

Kok Wai Wong

Keyword(s):

Neural Networks ◽

Mineral Prospectivity

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Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines

Ore Geology Reviews ◽

10.1016/j.oregeorev.2015.01.001 ◽

2015 ◽

Vol 71 ◽

pp. 804-818 ◽

Cited By ~ 226

Author(s):

V. Rodriguez-Galiano ◽

M. Sanchez-Castillo ◽

M. Chica-Olmo ◽

M. Chica-Rivas

Keyword(s):

Machine Learning ◽

Neural Networks ◽

Support Vector Machines ◽

Random Forest ◽

Predictive Models ◽

Regression Trees ◽

Support Vector ◽

Random Forest Regression ◽

Vector Machines ◽

Mineral Prospectivity

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Mineral Prospectivity Prediction via Convolutional Neural Networks Based on Geological Big Data

Journal of Earth Science ◽

10.1007/s12583-020-1365-z ◽

2021 ◽

Vol 32 (2) ◽

pp. 327-347

Author(s):

Shi Li ◽

Jianping Chen ◽

Chang Liu ◽

Yang Wang

Keyword(s):

Neural Networks ◽

Big Data ◽

Convolutional Neural Networks ◽

Mineral Prospectivity

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Assessing the effects of mineral systems-derived exploration targeting criteria for Random Forests-based predictive mapping of mineral prospectivity in Ahar-Arasbaran area, Iran

Ore Geology Reviews ◽

10.1016/j.oregeorev.2021.104399 ◽

2021 ◽

pp. 104399

Author(s):

Mohammad Parsa ◽

Abbas Maghsoudi

Keyword(s):

Random Forests ◽

Predictive Mapping ◽

Mineral Prospectivity

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Predictive Mapping of the Nodule Abundance and Mineral Resource Estimation in the Clarion-Clipperton Zone Using Artificial Neural Networks and Classical Geostatistical Methods

Deep-Sea Mining ◽

10.1007/978-3-319-52557-0_6 ◽

2017 ◽

pp. 189-212 ◽

Cited By ~ 5

Author(s):

Andreas Knobloch ◽

Thomas Kuhn ◽

Carsten Rühlemann ◽

Thomas Hertwig ◽

Karl-Otto Zeissler ◽

...

Keyword(s):

Neural Networks ◽

Mineral Resource ◽

Artificial Neural Networks ◽

Resource Estimation ◽

Predictive Mapping ◽

Geostatistical Methods ◽

Artificial Neural

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Modulating the Impacts of Stochastic Uncertainties Linked to Deposit Locations in Data-Driven Predictive Mapping of Mineral Prospectivity

Natural Resources Research ◽

10.1007/s11053-021-09891-9 ◽

2021 ◽

Author(s):

Mohammad Parsa ◽

Emmanuel John M. Carranza

Keyword(s):

Data Driven ◽

Predictive Mapping ◽

Mineral Prospectivity ◽

Stochastic Uncertainties

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