Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations
Само за регистроване кориснике
2008
Конференцијски прилог (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Some of the most commonly occuring problems in radioecological and environmental
radioactivitiy studies when applying traditional statistical models are multivariate and
multiscale structures of data. Spatial data analysis of radioactively contaminated areas are
particularly complex for many reasons: uncertainty of the source term, high spatial and
temporal variability of pollution patterns, spatial and temporal nonstationarity and
multivariate nature of the phenomenon with linearly and nonlinearly correlated variables.
There are only few studies on employing the multivariate approach to describe the correlation
between locations and radioactive contamination (Kanevski, 1996; Kanevski, 1997).
In this work the feasibility of using multivariate analysis techniques, principal component
analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft
independent modelling of class analogy (SIMCA) and artificial neural networks (ANN), to
predict soils and bioi...ndicators origin based on their radionuclide content was examined.
Извор:
Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway, 2008, 107-110Издавач:
- Østerås : Norwegian Radiation Protection Authority
Финансирање / пројекти:
- Нове методе и технике за сепарацију и специјацију хемијских елемената у траговима, органских супстанци и радионуклида и идентификацију њихових извора (RS-MESTD-MPN2006-2010-142039)
Институција/група
Tehnološko-metalurški fakultetTY - CONF AU - Dragović, Snežana AU - Momčilović, Milan AU - Onjia, Antonije PY - 2008 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/7185 AB - Some of the most commonly occuring problems in radioecological and environmental radioactivitiy studies when applying traditional statistical models are multivariate and multiscale structures of data. Spatial data analysis of radioactively contaminated areas are particularly complex for many reasons: uncertainty of the source term, high spatial and temporal variability of pollution patterns, spatial and temporal nonstationarity and multivariate nature of the phenomenon with linearly and nonlinearly correlated variables. There are only few studies on employing the multivariate approach to describe the correlation between locations and radioactive contamination (Kanevski, 1996; Kanevski, 1997). In this work the feasibility of using multivariate analysis techniques, principal component analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural networks (ANN), to predict soils and bioindicators origin based on their radionuclide content was examined. PB - Østerås : Norwegian Radiation Protection Authority C3 - Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway T1 - Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations EP - 110 SP - 107 UR - https://hdl.handle.net/21.15107/rcub_technorep_7185 ER -
@conference{ author = "Dragović, Snežana and Momčilović, Milan and Onjia, Antonije", year = "2008", abstract = "Some of the most commonly occuring problems in radioecological and environmental radioactivitiy studies when applying traditional statistical models are multivariate and multiscale structures of data. Spatial data analysis of radioactively contaminated areas are particularly complex for many reasons: uncertainty of the source term, high spatial and temporal variability of pollution patterns, spatial and temporal nonstationarity and multivariate nature of the phenomenon with linearly and nonlinearly correlated variables. There are only few studies on employing the multivariate approach to describe the correlation between locations and radioactive contamination (Kanevski, 1996; Kanevski, 1997). In this work the feasibility of using multivariate analysis techniques, principal component analysis (PCA), linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural networks (ANN), to predict soils and bioindicators origin based on their radionuclide content was examined.", publisher = "Østerås : Norwegian Radiation Protection Authority", journal = "Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway", title = "Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations", pages = "110-107", url = "https://hdl.handle.net/21.15107/rcub_technorep_7185" }
Dragović, S., Momčilović, M.,& Onjia, A.. (2008). Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations. in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway Østerås : Norwegian Radiation Protection Authority., 107-110. https://hdl.handle.net/21.15107/rcub_technorep_7185
Dragović S, Momčilović M, Onjia A. Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations. in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway. 2008;:107-110. https://hdl.handle.net/21.15107/rcub_technorep_7185 .
Dragović, Snežana, Momčilović, Milan, Onjia, Antonije, "Use of multivariate analysis in radioecological and environmental radoactivity studies - advantages and limitations" in Proceedings, oral and oral poster presentations / The International Conference on Radioecology & Environmental Radioactivity, 15-20 June, 2008, Bergen, Norway (2008):107-110, https://hdl.handle.net/21.15107/rcub_technorep_7185 .