Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments
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 (delta (CPDB)-P-13) 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.
Keywords:
oil-type pollution / sediments / artificial neural networks / n-alkane distribution / carbon isotope ratioSource:
Fresenius Environmental Bulletin, 1998, 7, 11-12, 648-653Publisher:
- Inst Lebensmitteltechnologie Analytische Chemie, Freising-Weihenstephan
Collections
Institution/Community
Hemijski fakultet / Faculty of ChemistryTY - JOUR AU - Micic, M AU - Jovančićević, Branimir AU - Polić, Predrag S. AU - Susic, N AU - Marković, Dragan A. PY - 1998 UR - https://cherry.chem.bg.ac.rs/handle/123456789/397 AB - 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 (delta (CPDB)-P-13) 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. PB - Inst Lebensmitteltechnologie Analytische Chemie, Freising-Weihenstephan T2 - Fresenius Environmental Bulletin T1 - Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments VL - 7 IS - 11-12 SP - 648 EP - 653 UR - https://hdl.handle.net/21.15107/rcub_cherry_397 ER -
@article{ author = "Micic, M and Jovančićević, Branimir and Polić, Predrag S. and Susic, N and Marković, Dragan A.", year = "1998", 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 (delta (CPDB)-P-13) 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.", publisher = "Inst Lebensmitteltechnologie Analytische Chemie, Freising-Weihenstephan", journal = "Fresenius Environmental Bulletin", title = "Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments", volume = "7", number = "11-12", pages = "648-653", url = "https://hdl.handle.net/21.15107/rcub_cherry_397" }
Micic, M., Jovančićević, B., Polić, P. S., Susic, N.,& Marković, D. A.. (1998). Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments. in Fresenius Environmental Bulletin Inst Lebensmitteltechnologie Analytische Chemie, Freising-Weihenstephan., 7(11-12), 648-653. https://hdl.handle.net/21.15107/rcub_cherry_397
Micic M, Jovančićević B, Polić PS, Susic N, Marković DA. Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments. in Fresenius Environmental Bulletin. 1998;7(11-12):648-653. https://hdl.handle.net/21.15107/rcub_cherry_397 .
Micic, M, Jovančićević, Branimir, Polić, Predrag S., Susic, N, Marković, Dragan A., "Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments" in Fresenius Environmental Bulletin, 7, no. 11-12 (1998):648-653, https://hdl.handle.net/21.15107/rcub_cherry_397 .