dc.creator | Mićić, M. | |
dc.creator | Jovančićević, B. | |
dc.creator | Polić, P. | |
dc.creator | Šušić, Nenad | |
dc.creator | Marković, D. | |
dc.date.accessioned | 2022-04-18T14:56:03Z | |
dc.date.available | 2022-04-18T14:56:03Z | |
dc.date.issued | 1998 | |
dc.identifier.issn | 1018-4619 | |
dc.identifier.uri | http://rims.institutims.rs/handle/123456789/13 | |
dc.description.abstract | The distinction between autochthonous, and oil-like origin of organic matter in geological sediments can be performed on the basis of n-alkane abundance and distribution patterns, determined by gas chromatography, or on the basis of the carbon-isotope ratio (δC13PDB) patterns of dominant n-alkanes, determined by gas chromatography-mass spectroscopy. Here we present solutions for automatic classification of organic matter origin in geological sediments, based on artificial neural networks. | en |
dc.publisher | TU Munchen | |
dc.rights | restrictedAccess | |
dc.source | Fresenius Environmental Bulletin | |
dc.subject | Sediments | en |
dc.subject | Oil-type pollution | en |
dc.subject | n-alkane distribution | en |
dc.subject | Carbon isotope ratio | en |
dc.subject | Artificial neural networks | en |
dc.title | Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments | en |
dc.type | article | |
dc.rights.license | ARR | |
dc.citation.epage | 653 | |
dc.citation.issue | 11-12 | |
dc.citation.other | 7(11-12): 648-653 | |
dc.citation.rank | M23 | |
dc.citation.spage | 648 | |
dc.citation.volume | 7 | |
dc.identifier.rcub | https://hdl.handle.net/21.15107/rcub_rims_13 | |
dc.identifier.scopus | 2-s2.0-0031729552 | |
dc.type.version | publishedVersion | |