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Zuo, Renguang (2017) Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods. Natural Resources Research, 26 (4) 457-464 doi:10.1007/s11053-017-9345-4

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Reference TypeJournal (article/letter/editorial)
TitleMachine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods
JournalNatural Resources Research
AuthorsZuo, RenguangAuthor
Year2017 (October)Volume26
Issue4
PublisherSpringer Science and Business Media LLC
DOIdoi:10.1007/s11053-017-9345-4Search in ResearchGate
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Mindat Ref. ID12914907Long-form Identifiermindat:1:5:12914907:3
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Full ReferenceZuo, Renguang (2017) Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods. Natural Resources Research, 26 (4) 457-464 doi:10.1007/s11053-017-9345-4
Plain TextZuo, Renguang (2017) Machine Learning of Mineralization-Related Geochemical Anomalies: A Review of Potential Methods. Natural Resources Research, 26 (4) 457-464 doi:10.1007/s11053-017-9345-4
In(2017, October) Natural Resources Research Vol. 26 (4) Springer Science and Business Media LLC

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Zuo, Renguang (2020) Geodata Science-Based Mineral Prospectivity Mapping: A Review. Natural Resources Research, 29 (6) 3415-3424 doi:10.1007/s11053-020-09700-9
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