Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods
Samo za registrovane korisnike
2007
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Multivariate data analysis methods were used to recognize and classify soils of unknown geographic origin. A total of 103 soil samples were differentiated into classes, according to regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232 and Be-7) activities detected by gamma-ray spectrometry were then used as the inputs in different pattern recognition methods. For the classification of soil samples using eight selected radionuclides, the prediction ability of linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) were 82.8%, 88.6%, 60.0% and 92.1%, respectively.
Ključne reči:
radionuclides / soil classification / multivariate analysis / LDA / kNN / SIMCA / ANNIzvor:
Applied Radiation and Isotopes, 2007, 65, 2, 218-224Izdavač:
- Pergamon-Elsevier Science Ltd, Oxford
Finansiranje / projekti:
- Nove metode i tehnike za separaciju i specijaciju hemijskih elemenata u tragovima, organskih supstanci i radionuklida i identifikaciju njihovih izvora (RS-MESTD-MPN2006-2010-142039)
DOI: 10.1016/j.apradiso.2006.07.005
ISSN: 0969-8043
PubMed: 16928448
WoS: 000243670300010
Scopus: 2-s2.0-37249023520
Institucija/grupa
Tehnološko-metalurški fakultetTY - JOUR AU - Dragović, Snežana AU - Onjia, Antonije PY - 2007 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1121 AB - Multivariate data analysis methods were used to recognize and classify soils of unknown geographic origin. A total of 103 soil samples were differentiated into classes, according to regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232 and Be-7) activities detected by gamma-ray spectrometry were then used as the inputs in different pattern recognition methods. For the classification of soil samples using eight selected radionuclides, the prediction ability of linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) were 82.8%, 88.6%, 60.0% and 92.1%, respectively. PB - Pergamon-Elsevier Science Ltd, Oxford T2 - Applied Radiation and Isotopes T1 - Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods EP - 224 IS - 2 SP - 218 VL - 65 DO - 10.1016/j.apradiso.2006.07.005 ER -
@article{ author = "Dragović, Snežana and Onjia, Antonije", year = "2007", abstract = "Multivariate data analysis methods were used to recognize and classify soils of unknown geographic origin. A total of 103 soil samples were differentiated into classes, according to regions in Serbia and Montenegro from which they were collected. Their radionuclide (Ra-226, U-238, U-235, K-40, Cs-134, Cs-137, Th-232 and Be-7) activities detected by gamma-ray spectrometry were then used as the inputs in different pattern recognition methods. For the classification of soil samples using eight selected radionuclides, the prediction ability of linear discriminant analysis (LDA), k-nearest neighbours (kNN), soft independent modelling of class analogy (SIMCA) and artificial neural network (ANN) were 82.8%, 88.6%, 60.0% and 92.1%, respectively.", publisher = "Pergamon-Elsevier Science Ltd, Oxford", journal = "Applied Radiation and Isotopes", title = "Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods", pages = "224-218", number = "2", volume = "65", doi = "10.1016/j.apradiso.2006.07.005" }
Dragović, S.,& Onjia, A.. (2007). Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods. in Applied Radiation and Isotopes Pergamon-Elsevier Science Ltd, Oxford., 65(2), 218-224. https://doi.org/10.1016/j.apradiso.2006.07.005
Dragović S, Onjia A. Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods. in Applied Radiation and Isotopes. 2007;65(2):218-224. doi:10.1016/j.apradiso.2006.07.005 .
Dragović, Snežana, Onjia, Antonije, "Classification of soil samples according to geographic origin using gamma-ray spectrometry and pattern recognition methods" in Applied Radiation and Isotopes, 65, no. 2 (2007):218-224, https://doi.org/10.1016/j.apradiso.2006.07.005 . .