Predicting ore content throughout a machine learning procedure – An Sn-W enrichment case study-Reference-Cited by-同舟云学术

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Predicting ore content throughout a machine learning procedure – An Sn-W enrichment case study

Published:2020-01 Issue: Volume:208 Page:106405
ISSN:0375-6742
Container-title:Journal of Geochemical Exploration
language:en
Short-container-title:Journal of Geochemical Exploration

Author:

Iglesias C.,Antunes I.M.H.R.,Albuquerque M.T.D.,Martínez J.,Taboada J.

Funder

Ministry of Education, Culture and Sports

ICT

FCT

COMPETE

Publisher

Elsevier BV

Subject

Economic Geology,Geochemistry and Petrology

Reference57 articles.

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2. Spatial risk assessment related to abandoned mining activities: an environmental management tool;Antunes;Environ. Earth Sci.,2014

3. Testing the predictive performance of distribution models;Bahn;Oikos,2013

4. Support vector machines for landslide susceptibility mapping: the Staffora River Basin case study, Italy;Ballabio;Math. Geosci.,2012

5. Robust linear programming discrimination of two linearly inseparable sets;Bennett;Optimization Methods and Software,1992

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1. Estimation of the dolomite content of carbonate rock outcrops based on spectral knowledge and machine learning;Frontiers in Earth Science;2024-06-11

2. Mineral exploration employing drones, contemporary geological satellite remote sensing and geographical information system (GIS) procedures: A review;Remote Sensing Applications: Society and Environment;2023-08

3. Error reduction in long-term mine planning estimates using deep learning models;Expert Systems with Applications;2023-05

4. Machine Learning Prediction of Ore Deposit Genetic Type Using Magnetite Geochemistry;Natural Resources Research;2022-12-12

5. A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications;Applied Geochemistry;2022-05

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