Analysis of the Samples with an Unknown Matrix Using Data Mining Algorithms

Autor:	E. N. Korzhova, V. V. Kuz’min, E. I. Molchanova, T. V. Stepanova
Rok vydání:	2017
Předmět:	Analyte Materials science Spectrometer General Chemical Engineering Metals and Alloys Regression analysis Welding Filter (signal processing) law.invention Inorganic Chemistry Matrix (chemical analysis) law Materials Chemistry Cluster analysis Biological system Intensity (heat transfer)
Zdroj:	Inorganic Materials. 53:1454-1457
ISSN:	1608-3172 0020-1685
DOI:	10.1134/s0020168517140138
Popis:	In determining a limited number of analytes in samples having a complex chemical composition with an unknown matrix, the combination of data mining algorithms (problems of clustering and regression) is proposed. This makes it possible to compensate for the influence of the components of the host medium on the intensity of the analytical line of an element being determined. The technology developed is tested in the X-ray fluorescence determination of S, Fe, Cu, Zn, and As in float concentrate samples during processing of polymetallic ores and V and Fe in synthetic film samples that are adequate in physicochemical properties to samples of welding fumes deposited on a filter. The error of the results of analysis has decreased by a factor 1.5–5 compared to the use of the Lucas-Tooth classical regression equation. The developed technology considerably increases the rapidity of analysis when it is used with X-ray spectrometers of consecutive action.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5032ac65491ccdf9be8361fd18939c3a https://doi.org/10.1134/s0020168517140138 Zobrazit plný text záznamu Plný text ve formátu PDF