Isaac Scientific Publishing

Journal of Advances in Applied Physics

Reducing Temperature Calibration Error in Multivariate Analysis of Fluorescence Spectra

Download PDF (354.9 KB) PP. 9 - 14 Pub. Date: February 1, 2020

DOI: 10.22606/jaap.2020.21002

Author(s)

  • Mikhail Khodasevich*
    B.I.Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus
  • Vladimir Aseev
    National Research University of Information Technologies, Mechanics, and Optics, St. Petersburg, Russia
  • Victor Klinkov
    Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
  • Evgenia Tsimerman
    Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
  • Darya Borisevich
    B.I.Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus

Abstract

A method has been demonstrated to reduce temperature calibration error by integrated using principal component analysis, hierarchical cluster analysis and searching combination moving window interval projection to latent structures for fluorescent spectra of Er-doped 98MgCaSrBaYAl2F14-2Ba(PO3)2 and Yb-doped CaF2. The consecutive and consistent use of these multivariate methods for outliers detection, forming training and test datasets and variable selection is shown to allow more than twofold reducing the root-mean-square error of temperature calibration in comparison with the application of projection to latent structures without variable selection.

Keywords

Projection to latent structures, principal component analysis, cluster analysis, calibration, fluorescence spectrum.

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