The Use of Principle Component Analysis in Type Classification of Air-dry Peat; IOP Conference Series: Earth and Environmental Science; Vol. 21: XVIII International Scientific Symposium in Honour of Academician M. A. Usov: Problems of Geology and Subsurface Development 7–11 April 2014, Tomsk, Russia

Bibliographische Detailangaben
Parent link:IOP Conference Series: Earth and Environmental Science
Vol. 21: XVIII International Scientific Symposium in Honour of Academician M. A. Usov: Problems of Geology and Subsurface Development 7–11 April 2014, Tomsk, Russia.— 2014.— [012045, 5 p.]
1. Verfasser: Chukhareva N. V. Natalia Vyacheslavovna
Körperschaft: Национальный исследовательский Томский политехнический университет (ТПУ) Институт природных ресурсов (ИПР) Кафедра транспорта и хранения нефти и газа (ТХНГ)
Weitere Verfasser: Zarubin A. G. Aleksey Gennadievich, Bulgakova O.
Zusammenfassung:Title screen
The Use of Principle Component Analysis in Type Classification of Air-dry Peat The use of principle component analysis (PCA) in the variant of projection on latent values with discriminant analysis (PLS-DA) in type classification of Siberian region air-dry peat by a set of properties is presented. A statistical analysis in principle component space by PCA of different physico-chemical properties of peat such as component composition, concentration of paramagnetic centers and IR-spectra is presented and shows a developed PLSDA classification model allows estimating peat type by a set of physico-chemical properties with minimum prediction errors.
Режим доступа: по договору с организацией-держателем ресурса
Sprache:Englisch
Veröffentlicht: 2014
Schriftenreihe:Comprehensive Utilization of Mineral Resources
Schlagworte:
Online-Zugang:http://iopscience.iop.org/1755-1315/21/1/012045
Format: MixedMaterials Elektronisch Buchkapitel
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=638295

MARC

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330 |a The Use of Principle Component Analysis in Type Classification of Air-dry Peat The use of principle component analysis (PCA) in the variant of projection on latent values with discriminant analysis (PLS-DA) in type classification of Siberian region air-dry peat by a set of properties is presented. A statistical analysis in principle component space by PCA of different physico-chemical properties of peat such as component composition, concentration of paramagnetic centers and IR-spectra is presented and shows a developed PLSDA classification model allows estimating peat type by a set of physico-chemical properties with minimum prediction errors. 
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