Journal
MATHEMATICAL GEOSCIENCES
Volume 42, Issue 6, Pages 681-703Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11004-010-9288-3
Keywords
Self-organising maps; Factor analysis; Celje; Mezica; Heavy metals; Compositional data processing
Funding
- Slovenian Agency for Research (research groups: Geochemistry and Underground Waters and Sedimentology and Mineral Resources)
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Two approaches, factor analysis (FA) and self-organising maps (SOM), have been used for the determination of geochemical associations in the two case studies evaluated here. In both case studies, different associations of elements, derived from different anthropogenic sources (smelters, ironworks, and chemical industry), are presented, together with natural associations of elements, all representing different geological environments. FA and SOM give similar results, despite some differences. Most similarities were achieved with the group of elements affected by strong pollution caused by smelting activities. The biggest difference between the two is that SOM can combine different groups into one, especially in the case of associations of elements connected with mild pollution (ironworking, chemical industry). The biggest advantage of SOM as opposed to FA is that SOM allow us to process variables, which are not normally distributed, or even of attributive nature. The use of such variables in SOM classification to prove the origins of associations of elements is also demonstrated here.
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