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.
