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  • 标题:3D Metallogenic Prediction Research based on GFH Analysis Method
  • 本地全文:下载
  • 作者:Song Huang ; Yuling Xie ; Huaming An
  • 期刊名称:IAENG International Journal of Computer Science
  • 印刷版ISSN:1819-656X
  • 电子版ISSN:1819-9224
  • 出版年度:2019
  • 卷号:46
  • 期号:4
  • 页码:699-706
  • 出版社:IAENG - International Association of Engineers
  • 摘要:In this paper, we systematically developed athree-dimensional quantitative metallogenic prognosis systemfor concealed ore bodies based on spatial data mining. Wecollected detailed geology information and constructed amultiple-source geology database. Based on the geologydatabase, major ore-controlling factors were defined usingcorrelation analysis between current mineralized ore bodiesand all related geology information, which included strata,faults, mineralization, mineral density, geophysics,geochemistry, etc. The new Grey-Fuzzy-Hierarchy (GFH)analysis method, a typical combined method including Greyrelational, Fuzzy comprehensive evaluation and Hierarchyanalytic process theories, was applied for the determination ofthe corresponding weights for all major ore-controlling factors.Finally, mineralization advantage degree (MAD) values wereobtained and the three potential mineralization target areaswere determined. Related high MAD value blocks were visuallydisplayed and reported as the guide of future explorationstrategy. The research achievements can also be used as areference for further research on 3D metallogenic predictionfields.
  • 关键词:Metallogenic prediction; Ore-controlling;factor; Correlation analysis; Grey rational analysis; Fuzzy;theory; Hierarchy analysis
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