Hunting for Geochemical Associations of Elements: Factor Analysis and Self-Organising Maps

被引:42
作者
Zibret, Gorazd [1 ]
Sajn, Robert [1 ]
机构
[1] Geol Survey Slovenia, Ljubljana 1000, Slovenia
关键词
Self-organising maps; Factor analysis; Celje; Mezica; Heavy metals; Compositional data processing; HEAVY-METAL AVAILABILITY; COMPOSITIONAL DATA; ATTIC-DUST; NEURAL-NETWORKS; TEMPORAL VARIATION; SOIL; SEDIMENT; CLASSIFICATION; FLOODPLAIN; IDRIJA;
D O I
10.1007/s11004-010-9288-3
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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.
引用
收藏
页码:681 / 703
页数:23
相关论文
共 53 条
[1]  
Abdi H., 2003, Encyclopedia of social sciences research methods, P978
[2]   Logratio analysis and compositional distance [J].
Aitchison, J ;
Barceló-Vidal, C ;
Martín-Fernández, JA ;
Pawlowsky-Glahn, V .
MATHEMATICAL GEOLOGY, 2000, 32 (03) :271-275
[3]   Assessment of Self-Organizing Map artificial neural networks for the classification of sediment quality [J].
Alvarez-Guerra, Manuel ;
Gonzalez-Pinuela, Cristina ;
Andres, Ana ;
Galan, Berta ;
Viguri, Javier R. .
ENVIRONMENT INTERNATIONAL, 2008, 34 (06) :782-790
[4]  
Anderson T.W., 1986, STAT ANAL DATA, V2nd, DOI DOI 10.1007/978-94-009-4109-0
[5]  
[Anonymous], 2007, Lecture Notes on Compositional Data Analysis
[6]   Assessment of metal contamination in dregded sediments using fractionation and Self-Organizing Maps [J].
Arias, R. ;
Barona, A. ;
Ibarra-Berastegi, G. ;
Aranguiz, I. ;
Elias, A. .
JOURNAL OF HAZARDOUS MATERIALS, 2008, 151 (01) :78-85
[7]   Comparison of self-organizing maps classification approach with cluster and principal components analysis for large environmental data sets [J].
Astel, A. ;
Tsakouski, S. ;
Barbieri, P. ;
Simeonov, V. .
WATER RESEARCH, 2007, 41 (19) :4566-4578
[8]  
Badran F., 2005, P379, DOI 10.1007/3-540-28847-3_7
[9]   Effects of spatial and temporal variation in metal availability on earthworms in floodplain soils of the river Dommel, The Netherlands [J].
Bleeker, Eric A. J. ;
van Gestel, Cornelis A. M. .
ENVIRONMENTAL POLLUTION, 2007, 148 (03) :824-832
[10]  
Child D., 2006, ESSENTIALS FACTOR AN, P180