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Determination of Gas Temperature in a CVD Reactor from Optical Emmission Spectra with the Help of Artificial Neural Networks and Group Method of Data Handling (GMDH)

  • S. A. Dolenko
  • A. V. Filippov
  • A. F. Pal
  • I. G. Persiantsev
  • A. O. Serov

Abstract

Optical emission spectroscopy is widely used for monitoring of low-temperature plasmas in science and technology [1]. However, determination of temperature from optical emission spectra is an inverse problem that is often very difficult to solve steadily by conventional methods. This paper reports successful application of artificial neural networks (ANN) and group method of data handling (GMDH) for determination of gas temperature from model optical emission spectra analogous to those recorded in a DC-discharge CVD reactor used for diamond film deposition.

Keywords

Artificial Neural Network Model Spectrum General Regression Neural Network Temperature Determination Chemical Vapour Deposition Reactor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 1998

Authors and Affiliations

  • S. A. Dolenko
    • 1
  • A. V. Filippov
    • 2
  • A. F. Pal
    • 1
  • I. G. Persiantsev
    • 1
  • A. O. Serov
    • 1
  1. 1.Microelectronics Dept., Nuclear Physics InstituteMoscow State UniversityMoscowRussia
  2. 2.Troitsk Institute of Innovation and Fusion ResearchTroitskRussia

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