Performance evaluation of RBF- and SVM-based machine learning algorithms for predictive mineral prospectivity modeling: integration of S-A multifractal model and ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01-03

AUTHORS

Reza Ghezelbash, Abbas Maghsoudi, Emmanuel John M. Carranza

ABSTRACT

Definition of the efficient ore-forming processes, which are considered as mineralization controls is a fundamental stage in mineral prospectivity modeling. In this contribution, four efficient targeting criteria of geochemical, geological and structural data related to porphyry-type Cu deposits in Varzaghan district, NW Iran, were integrated. For creation of multi-element geochemical layer, a two-stage factor analysis was firstly conducted on ilr-transformed data of 18 selected elements and it was found that factor 1 (F1) is the representative of Cu-Au-Mo-Bi elemental association in the study area. Then, the combined model of multifractal inverse distance weighting (IDW) interpolation technique and spectrum-area (S-A) fractal method of F1 as the significant mineralization-related multi-element geochemical layer was integrated with geological-structural evidence layers. For this purpose, two supervised machine learning algorithms, namely radial basis function (RBF) neural network and support vector machine (SVM) with RBF kernel were used for generating data-driven predictive models of porphyry-Cu mineral prospectivity. Comparison of the generated models demonstrates that the former is more successful in delineating exploration targets than the latter one. More... »

PAGES

1-17

References to SciGraph publications

  • 2017-10. Random Forest-Based Prospectivity Modelling of Greenfield Terrains Using Sparse Deposit Data: An Example from the Tanami Region, Western Australia in NATURAL RESOURCES RESEARCH
  • 2017-10. Natural Resources Research Publications on Geochemical Anomaly and Mineral Potential Mapping, and Introduction to the Special Issue of Papers in These Fields in NATURAL RESOURCES RESEARCH
  • 2002-03. Where Are Porphyry Copper Deposits Spatially Localized? A Case Study in Benguet Province, Philippines in NATURAL RESOURCES RESEARCH
  • 2000-03. Integrated Spatial and Spectrum Method for Geochemical Anomaly Separation in NATURAL RESOURCES RESEARCH
  • 2003-12. A Comparative Analysis of Favorability Mappings by Weights of Evidence, Probabilistic Neural Networks, Discriminant Analysis, and Logistic Regression in NATURAL RESOURCES RESEARCH
  • 2019-01-01. An Improved Data-Driven Multiple Criteria Decision-Making Procedure for Spatial Modeling of Mineral Prospectivity: Adaption of Prediction–Area Plot and Logistic Functions in NATURAL RESOURCES RESEARCH
  • 2008-03. Radial Basis Functional Link Nets Used as a Prospectivity Mapping Tool for Orogenic Gold Deposits Within the Central Lapland Greenstone Belt, Northern Fennoscandian Shield in NATURAL RESOURCES RESEARCH
  • 2017-10. Mineral Systems Analysis and Artificial Neural Network Modeling of Chromite Prospectivity in the Western Limb of the Bushveld Complex, South Africa in NATURAL RESOURCES RESEARCH
  • 2003-03. Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping in NATURAL RESOURCES RESEARCH
  • 2016-06. Comparison of the Data-Driven Random Forests Model and a Knowledge-Driven Method for Mineral Prospectivity Mapping: A Case Study for Gold Deposits Around the Huritz Group and Nueltin Suite, Nunavut, Canada in NATURAL RESOURCES RESEARCH
  • 2016-03. Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines) in NATURAL RESOURCES RESEARCH
  • 2004-09. Weights of Evidence Modeling of Mineral Potential: A Case Study Using Small Number of Prospects, Abra, Philippines in NATURAL RESOURCES RESEARCH
  • 2007-06. Application of Radial Basis Functional Link Networks to Exploration for Proterozoic Mineral Deposits in Central Iran in NATURAL RESOURCES RESEARCH
  • 2003-04. Isometric Logratio Transformations for Compositional Data Analysis in MATHEMATICAL GEOSCIENCES
  • 2005-03. Measuring the Performance of Mineral-Potential Maps in NATURAL RESOURCES RESEARCH
  • 2019-02. Prospectivity modeling of porphyry copper deposits: recognition of efficient mono- and multi-element geochemical signatures in the Varzaghan district, NW Iran in ACTA GEOCHIMICA
  • 1986. The Statistical Analysis of Compositional Data in NONE
  • 2016-06. Application of Discriminant Analysis and Support Vector Machine in Mapping Gold Potential Areas for Further Drilling in the Sari-Gunay Gold Deposit, NW Iran in NATURAL RESOURCES RESEARCH
  • 2014-03. A method for mineral prospectivity mapping integrating C4.5 decision tree, weights-of-evidence and m-branch smoothing techniques: a case study in the eastern Kunlun Mountains, China in EARTH SCIENCE INFORMATICS
  • 1995. The Nature of Statistical Learning Theory in NONE
  • 2018-06. A hybrid AHP-VIKOR approach for prospectivity modeling of porphyry Cu deposits in the Varzaghan District, NW Iran in ARABIAN JOURNAL OF GEOSCIENCES
  • 2015-12. A MATLAB-based program for processing geochemical data using fractal/multifractal modeling in EARTH SCIENCE INFORMATICS
  • 2005-06. Mapping Mineralization Probabilities using Multilayer Perceptrons in NATURAL RESOURCES RESEARCH
  • 2016-04. Decomposition of anomaly patterns of multi-element geochemical signatures in Ahar area, NW Iran: a comparison of U-spatial statistics and fractal models in ARABIAN JOURNAL OF GEOSCIENCES
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12145-018-00377-6

    DOI

    http://dx.doi.org/10.1007/s12145-018-00377-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111100833


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0403", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Geology", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/04", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Earth Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Amirkabir University of Technology", 
              "id": "https://www.grid.ac/institutes/grid.411368.9", 
              "name": [
                "Faculty of Mining and Metallurgical Engineering, Amirkabir University of Technology, Post Code: 15875-4413, Tehran, Iran"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ghezelbash", 
            "givenName": "Reza", 
            "id": "sg:person.013457265202.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013457265202.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Amirkabir University of Technology", 
              "id": "https://www.grid.ac/institutes/grid.411368.9", 
              "name": [
                "Faculty of Mining and Metallurgical Engineering, Amirkabir University of Technology, Post Code: 15875-4413, Tehran, Iran"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Maghsoudi", 
            "givenName": "Abbas", 
            "id": "sg:person.012063630051.34", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012063630051.34"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of KwaZulu-Natal", 
              "id": "https://www.grid.ac/institutes/grid.16463.36", 
              "name": [
                "Geological Sciences, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, South Africa"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Carranza", 
            "givenName": "Emmanuel John M.", 
            "id": "sg:person.013202650101.56", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013202650101.56"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s11053-015-9268-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001332250", 
              "https://doi.org/10.1007/s11053-015-9268-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/13658816.2014.885527", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002377165"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2014.10.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002696738"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2014.11.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003020534"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2015.01.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004022741"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0883-2927(01)00066-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004114696"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2011.11.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004452808"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-007-9036-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004515433", 
              "https://doi.org/10.1007/s11053-007-9036-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2009.11.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004818463"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.chemer.2013.07.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005101571"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/07038992.1991.10855292", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005503992"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2009.02.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005591308"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5194/bg-7-3019-2010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005655212"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2014.08.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006031024"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2015.01.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006203212"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2010.09.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006854689"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-008-9062-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007885914", 
              "https://doi.org/10.1007/s11053-008-9062-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1139/e81-019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007935984"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2008.08.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008246179"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12145-013-0128-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010202762", 
              "https://doi.org/10.1007/s12145-013-0128-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2475/ajs.304.1.1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011447403"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2006.12.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012307739"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2015.03.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012370899"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2012.02.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012774345"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0375-6742(99)00028-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013305023"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.landurbplan.2012.09.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017041848"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00206810903360422", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017319102"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jafrearsci.2016.11.021", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018589630"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.geoderma.2010.01.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018762319"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.apgeochem.2012.10.031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020568751"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jag.2009.06.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020598792"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.fss.2011.08.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021114454"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jseaes.2005.04.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021522376"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1023818214614", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024177181", 
              "https://doi.org/10.1023/a:1023818214614"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12517-016-2435-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024513823", 
              "https://doi.org/10.1007/s12517-016-2435-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12145-015-0215-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025301254", 
              "https://doi.org/10.1007/s12145-015-0215-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.chemer.2013.08.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025880809"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0191-8141(96)00032-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025883809"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2015.04.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026684111"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4757-2440-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027312764", 
              "https://doi.org/10.1007/978-1-4757-2440-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4757-2440-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027312764", 
              "https://doi.org/10.1007/978-1-4757-2440-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jog.2010.01.018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027724927"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0169-1368(87)90024-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027872835"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0169-1368(87)90024-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027872835"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2015.05.019", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029008459"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2011.03.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029859369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jafrearsci.2015.12.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030235614"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/01431160110040323", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031444258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2016.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033044277"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2005.08.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033146484"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1010109829861", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034561745", 
              "https://doi.org/10.1023/a:1010109829861"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:narr.0000046919.87758.f5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035088252", 
              "https://doi.org/10.1023/b:narr.0000046919.87758.f5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2011.12.014", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035493676"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jappgeo.2012.05.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036060062"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-015-9274-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036551574", 
              "https://doi.org/10.1007/s11053-015-9274-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1144/geochem2012-144", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036789125"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1014287720379", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040077972", 
              "https://doi.org/10.1023/a:1014287720379"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0883-2927(03)00083-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040154714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0883-2927(03)00083-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040154714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2011.06.012", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040224418"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2007.07.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040624364"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1022693220894", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041504882", 
              "https://doi.org/10.1023/a:1022693220894"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2015.03.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041602916"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2006.10.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041809047"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.gexplo.2012.04.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041819136"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-005-6955-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042381157", 
              "https://doi.org/10.1007/s11053-005-6955-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-005-6955-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042381157", 
              "https://doi.org/10.1007/s11053-005-6955-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1046/j.1440-0952.2000.00807.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043936966"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cageo.2015.03.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045064995"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jseaes.2012.10.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046370331"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0375-6742(94)90013-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046475343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0375-6742(94)90013-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046475343"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-005-4674-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048115051", 
              "https://doi.org/10.1007/s11053-005-4674-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-005-4674-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048115051", 
              "https://doi.org/10.1007/s11053-005-4674-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/00206810903416323", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050066550"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/b:narr.0000007804.27450.e8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050138855", 
              "https://doi.org/10.1023/b:narr.0000007804.27450.e8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2013.04.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050775885"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2014.12.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051593866"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-015-9271-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052834423", 
              "https://doi.org/10.1007/s11053-015-9271-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tgrs.1990.572988", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061608441"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2113/gsecongeo.100.5.801", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068925589"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2113/gsecongeo.105.1.3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068926130"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2113/gsecongeo.93.5.651", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068933838"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jag.2017.02.006", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083866132"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9335-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084981533", 
              "https://doi.org/10.1007/s11053-017-9335-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9335-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084981533", 
              "https://doi.org/10.1007/s11053-017-9335-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9344-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085573136", 
              "https://doi.org/10.1007/s11053-017-9344-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9344-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085573136", 
              "https://doi.org/10.1007/s11053-017-9344-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9348-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085756191", 
              "https://doi.org/10.1007/s11053-017-9348-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-017-9348-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085756191", 
              "https://doi.org/10.1007/s11053-017-9348-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.oregeorev.2017.11.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092687617"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.crte.2018.02.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103231727"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12517-018-3624-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104423610", 
              "https://doi.org/10.1007/s12517-018-3624-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12517-018-3624-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1104423610", 
              "https://doi.org/10.1007/s12517-018-3624-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11631-018-0289-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1105927461", 
              "https://doi.org/10.1007/s11631-018-0289-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-009-4109-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1109716595", 
              "https://doi.org/10.1007/978-94-009-4109-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-94-009-4109-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1109716595", 
              "https://doi.org/10.1007/978-94-009-4109-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11053-018-9448-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1111036535", 
              "https://doi.org/10.1007/s11053-018-9448-6"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-01-03", 
        "datePublishedReg": "2019-01-03", 
        "description": "Definition of the efficient ore-forming processes, which are considered as mineralization controls is a fundamental stage in mineral prospectivity modeling. In this contribution, four efficient targeting criteria of geochemical, geological and structural data related to porphyry-type Cu deposits in Varzaghan district, NW Iran, were integrated. For creation of multi-element geochemical layer, a two-stage factor analysis was firstly conducted on ilr-transformed data of 18 selected elements and it was found that factor 1 (F1) is the representative of Cu-Au-Mo-Bi elemental association in the study area. Then, the combined model of multifractal inverse distance weighting (IDW) interpolation technique and spectrum-area (S-A) fractal method of F1 as the significant mineralization-related multi-element geochemical layer was integrated with geological-structural evidence layers. For this purpose, two supervised machine learning algorithms, namely radial basis function (RBF) neural network and support vector machine (SVM) with RBF kernel were used for generating data-driven predictive models of porphyry-Cu mineral prospectivity. Comparison of the generated models demonstrates that the former is more successful in delineating exploration targets than the latter one.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s12145-018-00377-6", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1049211", 
            "issn": [
              "1865-0473", 
              "1865-0481"
            ], 
            "name": "Earth Science Informatics", 
            "type": "Periodical"
          }
        ], 
        "name": "Performance evaluation of RBF- and SVM-based machine learning algorithms for predictive mineral prospectivity modeling: integration of S-A multifractal model and mineralization controls", 
        "pagination": "1-17", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "1e43633d5977fc91e454c28bdfe2ff56f7d7bfde102c12cf31898fc81f69f488"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s12145-018-00377-6"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1111100833"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s12145-018-00377-6", 
          "https://app.dimensions.ai/details/publication/pub.1111100833"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T08:35", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000311_0000000311/records_55484_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs12145-018-00377-6"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12145-018-00377-6'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12145-018-00377-6'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12145-018-00377-6'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12145-018-00377-6'


     

    This table displays all metadata directly associated to this object as RDF triples.

    357 TRIPLES      21 PREDICATES      111 URIs      16 LITERALS      5 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s12145-018-00377-6 schema:about anzsrc-for:04
    2 anzsrc-for:0403
    3 schema:author Nfa78762d949c4d4ca637a2131d21d002
    4 schema:citation sg:pub.10.1007/978-1-4757-2440-0
    5 sg:pub.10.1007/978-94-009-4109-0
    6 sg:pub.10.1007/s11053-005-4674-0
    7 sg:pub.10.1007/s11053-005-6955-z
    8 sg:pub.10.1007/s11053-007-9036-7
    9 sg:pub.10.1007/s11053-008-9062-0
    10 sg:pub.10.1007/s11053-015-9268-x
    11 sg:pub.10.1007/s11053-015-9271-2
    12 sg:pub.10.1007/s11053-015-9274-z
    13 sg:pub.10.1007/s11053-017-9335-6
    14 sg:pub.10.1007/s11053-017-9344-5
    15 sg:pub.10.1007/s11053-017-9348-1
    16 sg:pub.10.1007/s11053-018-9448-6
    17 sg:pub.10.1007/s11631-018-0289-0
    18 sg:pub.10.1007/s12145-013-0128-0
    19 sg:pub.10.1007/s12145-015-0215-5
    20 sg:pub.10.1007/s12517-016-2435-5
    21 sg:pub.10.1007/s12517-018-3624-1
    22 sg:pub.10.1023/a:1010109829861
    23 sg:pub.10.1023/a:1014287720379
    24 sg:pub.10.1023/a:1022693220894
    25 sg:pub.10.1023/a:1023818214614
    26 sg:pub.10.1023/b:narr.0000007804.27450.e8
    27 sg:pub.10.1023/b:narr.0000046919.87758.f5
    28 https://doi.org/10.1016/0169-1368(87)90024-2
    29 https://doi.org/10.1016/0191-8141(96)00032-6
    30 https://doi.org/10.1016/0375-6742(94)90013-2
    31 https://doi.org/10.1016/j.apgeochem.2012.10.031
    32 https://doi.org/10.1016/j.cageo.2009.02.008
    33 https://doi.org/10.1016/j.cageo.2010.09.014
    34 https://doi.org/10.1016/j.cageo.2011.11.009
    35 https://doi.org/10.1016/j.cageo.2011.12.014
    36 https://doi.org/10.1016/j.cageo.2014.10.004
    37 https://doi.org/10.1016/j.cageo.2015.03.007
    38 https://doi.org/10.1016/j.chemer.2013.07.001
    39 https://doi.org/10.1016/j.chemer.2013.08.001
    40 https://doi.org/10.1016/j.crte.2018.02.003
    41 https://doi.org/10.1016/j.fss.2011.08.011
    42 https://doi.org/10.1016/j.geoderma.2010.01.009
    43 https://doi.org/10.1016/j.gexplo.2005.08.001
    44 https://doi.org/10.1016/j.gexplo.2008.08.003
    45 https://doi.org/10.1016/j.gexplo.2009.11.003
    46 https://doi.org/10.1016/j.gexplo.2011.03.005
    47 https://doi.org/10.1016/j.gexplo.2011.06.012
    48 https://doi.org/10.1016/j.gexplo.2012.02.002
    49 https://doi.org/10.1016/j.gexplo.2012.04.010
    50 https://doi.org/10.1016/j.gexplo.2014.11.015
    51 https://doi.org/10.1016/j.gexplo.2015.04.010
    52 https://doi.org/10.1016/j.gexplo.2016.03.009
    53 https://doi.org/10.1016/j.jafrearsci.2015.12.007
    54 https://doi.org/10.1016/j.jafrearsci.2016.11.021
    55 https://doi.org/10.1016/j.jag.2009.06.002
    56 https://doi.org/10.1016/j.jag.2017.02.006
    57 https://doi.org/10.1016/j.jappgeo.2012.05.003
    58 https://doi.org/10.1016/j.jog.2010.01.018
    59 https://doi.org/10.1016/j.jseaes.2005.04.005
    60 https://doi.org/10.1016/j.jseaes.2012.10.002
    61 https://doi.org/10.1016/j.landurbplan.2012.09.008
    62 https://doi.org/10.1016/j.oregeorev.2006.10.002
    63 https://doi.org/10.1016/j.oregeorev.2006.12.001
    64 https://doi.org/10.1016/j.oregeorev.2007.07.001
    65 https://doi.org/10.1016/j.oregeorev.2013.04.007
    66 https://doi.org/10.1016/j.oregeorev.2014.08.010
    67 https://doi.org/10.1016/j.oregeorev.2014.12.007
    68 https://doi.org/10.1016/j.oregeorev.2015.01.001
    69 https://doi.org/10.1016/j.oregeorev.2015.01.010
    70 https://doi.org/10.1016/j.oregeorev.2015.03.003
    71 https://doi.org/10.1016/j.oregeorev.2015.03.022
    72 https://doi.org/10.1016/j.oregeorev.2015.05.019
    73 https://doi.org/10.1016/j.oregeorev.2017.11.013
    74 https://doi.org/10.1016/s0375-6742(99)00028-x
    75 https://doi.org/10.1016/s0883-2927(01)00066-x
    76 https://doi.org/10.1016/s0883-2927(03)00083-0
    77 https://doi.org/10.1046/j.1440-0952.2000.00807.x
    78 https://doi.org/10.1080/00206810903360422
    79 https://doi.org/10.1080/00206810903416323
    80 https://doi.org/10.1080/01431160110040323
    81 https://doi.org/10.1080/07038992.1991.10855292
    82 https://doi.org/10.1080/13658816.2014.885527
    83 https://doi.org/10.1109/tgrs.1990.572988
    84 https://doi.org/10.1139/e81-019
    85 https://doi.org/10.1144/geochem2012-144
    86 https://doi.org/10.2113/gsecongeo.100.5.801
    87 https://doi.org/10.2113/gsecongeo.105.1.3
    88 https://doi.org/10.2113/gsecongeo.93.5.651
    89 https://doi.org/10.2475/ajs.304.1.1
    90 https://doi.org/10.5194/bg-7-3019-2010
    91 schema:datePublished 2019-01-03
    92 schema:datePublishedReg 2019-01-03
    93 schema:description Definition of the efficient ore-forming processes, which are considered as mineralization controls is a fundamental stage in mineral prospectivity modeling. In this contribution, four efficient targeting criteria of geochemical, geological and structural data related to porphyry-type Cu deposits in Varzaghan district, NW Iran, were integrated. For creation of multi-element geochemical layer, a two-stage factor analysis was firstly conducted on ilr-transformed data of 18 selected elements and it was found that factor 1 (F1) is the representative of Cu-Au-Mo-Bi elemental association in the study area. Then, the combined model of multifractal inverse distance weighting (IDW) interpolation technique and spectrum-area (S-A) fractal method of F1 as the significant mineralization-related multi-element geochemical layer was integrated with geological-structural evidence layers. For this purpose, two supervised machine learning algorithms, namely radial basis function (RBF) neural network and support vector machine (SVM) with RBF kernel were used for generating data-driven predictive models of porphyry-Cu mineral prospectivity. Comparison of the generated models demonstrates that the former is more successful in delineating exploration targets than the latter one.
    94 schema:genre research_article
    95 schema:inLanguage en
    96 schema:isAccessibleForFree false
    97 schema:isPartOf sg:journal.1049211
    98 schema:name Performance evaluation of RBF- and SVM-based machine learning algorithms for predictive mineral prospectivity modeling: integration of S-A multifractal model and mineralization controls
    99 schema:pagination 1-17
    100 schema:productId N8f11e9ddeb8244f1b1150d87641af73d
    101 Nad5480c551d342bebd0e55e66a28cc38
    102 Nf52f4ab02f37499c9d2100ecb2d4318f
    103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111100833
    104 https://doi.org/10.1007/s12145-018-00377-6
    105 schema:sdDatePublished 2019-04-11T08:35
    106 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    107 schema:sdPublisher N214baf73b52e4acfb7e14c62b98f9c70
    108 schema:url https://link.springer.com/10.1007%2Fs12145-018-00377-6
    109 sgo:license sg:explorer/license/
    110 sgo:sdDataset articles
    111 rdf:type schema:ScholarlyArticle
    112 N214baf73b52e4acfb7e14c62b98f9c70 schema:name Springer Nature - SN SciGraph project
    113 rdf:type schema:Organization
    114 N71af6265f4c748389562cc1b982e750b rdf:first sg:person.013202650101.56
    115 rdf:rest rdf:nil
    116 N8f11e9ddeb8244f1b1150d87641af73d schema:name doi
    117 schema:value 10.1007/s12145-018-00377-6
    118 rdf:type schema:PropertyValue
    119 N9744ac8d2a1b4487999d29d41231843c rdf:first sg:person.012063630051.34
    120 rdf:rest N71af6265f4c748389562cc1b982e750b
    121 Nad5480c551d342bebd0e55e66a28cc38 schema:name readcube_id
    122 schema:value 1e43633d5977fc91e454c28bdfe2ff56f7d7bfde102c12cf31898fc81f69f488
    123 rdf:type schema:PropertyValue
    124 Nf52f4ab02f37499c9d2100ecb2d4318f schema:name dimensions_id
    125 schema:value pub.1111100833
    126 rdf:type schema:PropertyValue
    127 Nfa78762d949c4d4ca637a2131d21d002 rdf:first sg:person.013457265202.14
    128 rdf:rest N9744ac8d2a1b4487999d29d41231843c
    129 anzsrc-for:04 schema:inDefinedTermSet anzsrc-for:
    130 schema:name Earth Sciences
    131 rdf:type schema:DefinedTerm
    132 anzsrc-for:0403 schema:inDefinedTermSet anzsrc-for:
    133 schema:name Geology
    134 rdf:type schema:DefinedTerm
    135 sg:journal.1049211 schema:issn 1865-0473
    136 1865-0481
    137 schema:name Earth Science Informatics
    138 rdf:type schema:Periodical
    139 sg:person.012063630051.34 schema:affiliation https://www.grid.ac/institutes/grid.411368.9
    140 schema:familyName Maghsoudi
    141 schema:givenName Abbas
    142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012063630051.34
    143 rdf:type schema:Person
    144 sg:person.013202650101.56 schema:affiliation https://www.grid.ac/institutes/grid.16463.36
    145 schema:familyName Carranza
    146 schema:givenName Emmanuel John M.
    147 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013202650101.56
    148 rdf:type schema:Person
    149 sg:person.013457265202.14 schema:affiliation https://www.grid.ac/institutes/grid.411368.9
    150 schema:familyName Ghezelbash
    151 schema:givenName Reza
    152 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013457265202.14
    153 rdf:type schema:Person
    154 sg:pub.10.1007/978-1-4757-2440-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027312764
    155 https://doi.org/10.1007/978-1-4757-2440-0
    156 rdf:type schema:CreativeWork
    157 sg:pub.10.1007/978-94-009-4109-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109716595
    158 https://doi.org/10.1007/978-94-009-4109-0
    159 rdf:type schema:CreativeWork
    160 sg:pub.10.1007/s11053-005-4674-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048115051
    161 https://doi.org/10.1007/s11053-005-4674-0
    162 rdf:type schema:CreativeWork
    163 sg:pub.10.1007/s11053-005-6955-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1042381157
    164 https://doi.org/10.1007/s11053-005-6955-z
    165 rdf:type schema:CreativeWork
    166 sg:pub.10.1007/s11053-007-9036-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004515433
    167 https://doi.org/10.1007/s11053-007-9036-7
    168 rdf:type schema:CreativeWork
    169 sg:pub.10.1007/s11053-008-9062-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007885914
    170 https://doi.org/10.1007/s11053-008-9062-0
    171 rdf:type schema:CreativeWork
    172 sg:pub.10.1007/s11053-015-9268-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1001332250
    173 https://doi.org/10.1007/s11053-015-9268-x
    174 rdf:type schema:CreativeWork
    175 sg:pub.10.1007/s11053-015-9271-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052834423
    176 https://doi.org/10.1007/s11053-015-9271-2
    177 rdf:type schema:CreativeWork
    178 sg:pub.10.1007/s11053-015-9274-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1036551574
    179 https://doi.org/10.1007/s11053-015-9274-z
    180 rdf:type schema:CreativeWork
    181 sg:pub.10.1007/s11053-017-9335-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084981533
    182 https://doi.org/10.1007/s11053-017-9335-6
    183 rdf:type schema:CreativeWork
    184 sg:pub.10.1007/s11053-017-9344-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085573136
    185 https://doi.org/10.1007/s11053-017-9344-5
    186 rdf:type schema:CreativeWork
    187 sg:pub.10.1007/s11053-017-9348-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085756191
    188 https://doi.org/10.1007/s11053-017-9348-1
    189 rdf:type schema:CreativeWork
    190 sg:pub.10.1007/s11053-018-9448-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111036535
    191 https://doi.org/10.1007/s11053-018-9448-6
    192 rdf:type schema:CreativeWork
    193 sg:pub.10.1007/s11631-018-0289-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105927461
    194 https://doi.org/10.1007/s11631-018-0289-0
    195 rdf:type schema:CreativeWork
    196 sg:pub.10.1007/s12145-013-0128-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010202762
    197 https://doi.org/10.1007/s12145-013-0128-0
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1007/s12145-015-0215-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025301254
    200 https://doi.org/10.1007/s12145-015-0215-5
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1007/s12517-016-2435-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024513823
    203 https://doi.org/10.1007/s12517-016-2435-5
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1007/s12517-018-3624-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104423610
    206 https://doi.org/10.1007/s12517-018-3624-1
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1023/a:1010109829861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034561745
    209 https://doi.org/10.1023/a:1010109829861
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1023/a:1014287720379 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040077972
    212 https://doi.org/10.1023/a:1014287720379
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1023/a:1022693220894 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041504882
    215 https://doi.org/10.1023/a:1022693220894
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1023/a:1023818214614 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024177181
    218 https://doi.org/10.1023/a:1023818214614
    219 rdf:type schema:CreativeWork
    220 sg:pub.10.1023/b:narr.0000007804.27450.e8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050138855
    221 https://doi.org/10.1023/b:narr.0000007804.27450.e8
    222 rdf:type schema:CreativeWork
    223 sg:pub.10.1023/b:narr.0000046919.87758.f5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035088252
    224 https://doi.org/10.1023/b:narr.0000046919.87758.f5
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1016/0169-1368(87)90024-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027872835
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1016/0191-8141(96)00032-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025883809
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.1016/0375-6742(94)90013-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046475343
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.1016/j.apgeochem.2012.10.031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020568751
    233 rdf:type schema:CreativeWork
    234 https://doi.org/10.1016/j.cageo.2009.02.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005591308
    235 rdf:type schema:CreativeWork
    236 https://doi.org/10.1016/j.cageo.2010.09.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006854689
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1016/j.cageo.2011.11.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004452808
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1016/j.cageo.2011.12.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035493676
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1016/j.cageo.2014.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002696738
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1016/j.cageo.2015.03.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045064995
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1016/j.chemer.2013.07.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005101571
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1016/j.chemer.2013.08.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025880809
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1016/j.crte.2018.02.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103231727
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1016/j.fss.2011.08.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021114454
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1016/j.geoderma.2010.01.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018762319
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1016/j.gexplo.2005.08.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033146484
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1016/j.gexplo.2008.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008246179
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1016/j.gexplo.2009.11.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004818463
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1016/j.gexplo.2011.03.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029859369
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1016/j.gexplo.2011.06.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040224418
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1016/j.gexplo.2012.02.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012774345
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1016/j.gexplo.2012.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041819136
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1016/j.gexplo.2014.11.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003020534
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.1016/j.gexplo.2015.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026684111
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.1016/j.gexplo.2016.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033044277
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.1016/j.jafrearsci.2015.12.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030235614
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.1016/j.jafrearsci.2016.11.021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018589630
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.1016/j.jag.2009.06.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020598792
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.1016/j.jag.2017.02.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083866132
    283 rdf:type schema:CreativeWork
    284 https://doi.org/10.1016/j.jappgeo.2012.05.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036060062
    285 rdf:type schema:CreativeWork
    286 https://doi.org/10.1016/j.jog.2010.01.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027724927
    287 rdf:type schema:CreativeWork
    288 https://doi.org/10.1016/j.jseaes.2005.04.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021522376
    289 rdf:type schema:CreativeWork
    290 https://doi.org/10.1016/j.jseaes.2012.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046370331
    291 rdf:type schema:CreativeWork
    292 https://doi.org/10.1016/j.landurbplan.2012.09.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017041848
    293 rdf:type schema:CreativeWork
    294 https://doi.org/10.1016/j.oregeorev.2006.10.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041809047
    295 rdf:type schema:CreativeWork
    296 https://doi.org/10.1016/j.oregeorev.2006.12.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012307739
    297 rdf:type schema:CreativeWork
    298 https://doi.org/10.1016/j.oregeorev.2007.07.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040624364
    299 rdf:type schema:CreativeWork
    300 https://doi.org/10.1016/j.oregeorev.2013.04.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050775885
    301 rdf:type schema:CreativeWork
    302 https://doi.org/10.1016/j.oregeorev.2014.08.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006031024
    303 rdf:type schema:CreativeWork
    304 https://doi.org/10.1016/j.oregeorev.2014.12.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051593866
    305 rdf:type schema:CreativeWork
    306 https://doi.org/10.1016/j.oregeorev.2015.01.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006203212
    307 rdf:type schema:CreativeWork
    308 https://doi.org/10.1016/j.oregeorev.2015.01.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004022741
    309 rdf:type schema:CreativeWork
    310 https://doi.org/10.1016/j.oregeorev.2015.03.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012370899
    311 rdf:type schema:CreativeWork
    312 https://doi.org/10.1016/j.oregeorev.2015.03.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041602916
    313 rdf:type schema:CreativeWork
    314 https://doi.org/10.1016/j.oregeorev.2015.05.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029008459
    315 rdf:type schema:CreativeWork
    316 https://doi.org/10.1016/j.oregeorev.2017.11.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092687617
    317 rdf:type schema:CreativeWork
    318 https://doi.org/10.1016/s0375-6742(99)00028-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1013305023
    319 rdf:type schema:CreativeWork
    320 https://doi.org/10.1016/s0883-2927(01)00066-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1004114696
    321 rdf:type schema:CreativeWork
    322 https://doi.org/10.1016/s0883-2927(03)00083-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040154714
    323 rdf:type schema:CreativeWork
    324 https://doi.org/10.1046/j.1440-0952.2000.00807.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043936966
    325 rdf:type schema:CreativeWork
    326 https://doi.org/10.1080/00206810903360422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017319102
    327 rdf:type schema:CreativeWork
    328 https://doi.org/10.1080/00206810903416323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050066550
    329 rdf:type schema:CreativeWork
    330 https://doi.org/10.1080/01431160110040323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031444258
    331 rdf:type schema:CreativeWork
    332 https://doi.org/10.1080/07038992.1991.10855292 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005503992
    333 rdf:type schema:CreativeWork
    334 https://doi.org/10.1080/13658816.2014.885527 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002377165
    335 rdf:type schema:CreativeWork
    336 https://doi.org/10.1109/tgrs.1990.572988 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061608441
    337 rdf:type schema:CreativeWork
    338 https://doi.org/10.1139/e81-019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007935984
    339 rdf:type schema:CreativeWork
    340 https://doi.org/10.1144/geochem2012-144 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036789125
    341 rdf:type schema:CreativeWork
    342 https://doi.org/10.2113/gsecongeo.100.5.801 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068925589
    343 rdf:type schema:CreativeWork
    344 https://doi.org/10.2113/gsecongeo.105.1.3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068926130
    345 rdf:type schema:CreativeWork
    346 https://doi.org/10.2113/gsecongeo.93.5.651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068933838
    347 rdf:type schema:CreativeWork
    348 https://doi.org/10.2475/ajs.304.1.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011447403
    349 rdf:type schema:CreativeWork
    350 https://doi.org/10.5194/bg-7-3019-2010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005655212
    351 rdf:type schema:CreativeWork
    352 https://www.grid.ac/institutes/grid.16463.36 schema:alternateName University of KwaZulu-Natal
    353 schema:name Geological Sciences, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Durban, South Africa
    354 rdf:type schema:Organization
    355 https://www.grid.ac/institutes/grid.411368.9 schema:alternateName Amirkabir University of Technology
    356 schema:name Faculty of Mining and Metallurgical Engineering, Amirkabir University of Technology, Post Code: 15875-4413, Tehran, Iran
    357 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...