Journal of Spectroscopy (Jan 2018)

Classification of Geological Samples Based on Soft Independent Modeling of Class Analogy Using Laser-Induced Breakdown Spectroscopy

  • Ying Zhang,
  • Ying Li,
  • Wendong Li,
  • Zigang Sun,
  • Yunfeng Bi

DOI
https://doi.org/10.1155/2018/3683089
Journal volume & issue
Vol. 2018

Abstract

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Laser-induced breakdown spectroscopy with soft independent modeling of class analogy is used in the identification of a large number of unprocessed geological samples having similar components in this study. Considering a variety of data from different samples, representative spectral regions representing the major components were extracted. In addition, principal component analysis was applied to remove noninformative variables from the spectrum. The unclassification rate, misclassification rate, and average correct classification rate for 25 types of geological samples were 1.2%, 4.7%, and 94.1%, respectively. These results suggest that laser-induced breakdown spectroscopy using soft independent modeling of class analogy can be used to identify a wide variety of geological samples. Furthermore, we found that this approach can be used to identify spectral differences among similar sample types because of matrix effects and the trace element impurities.