Study of ore deposits by the dynamic systems investigation methods: 2. Clustering of ore deposits and interpretation of the results View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-05

AUTHORS

M. V. Rodkin, A. R. Shatakhtsyan

ABSTRACT

Ore deposits are complex natural objects. Each deposit is unique in its own way. At the same time, efficient data processing for a large number of the deposits and better understanding of the ore formation processes require intensional clustering of the deposits. A series of schemes exists for clustering (classifying) the deposits depending on the set of the contained ore components and other parameters. We discuss the new formal ways for clustering the ore deposits based on the Tanimoto similarity measure (for the data on the set of the contained metal components) and on the mixed correlation dimension (for the data on the relative spatial locations of the deposits). We demonstrate the close correlation between the cross-similarity estimates calculated for different types of the deposits using the Tanimoto measure and mixed correlation dimension. We discuss the version of clustering the deposits based on the Tanimoto measure and suggest a tentative interpretation of a series of the formally identified statistical regularities. Some results of this clustering can be treated as an argument supporting the previous hypothesis which states that the formation of the large and extralarge ore deposits is a byproduct of the transformation of the material of the tectonosphere from one geochemical reservoir (upper continental crust, lower continental crust, oceanic crust, upper mantle, etc.) into another. The energy of these tectonic processes drives the massive negentgropy processes concentrating ore material into the deposits. More... »

PAGES

428-436

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s1069351315030143

DOI

http://dx.doi.org/10.1134/s1069351315030143

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017471000


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