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Physics of Particles and Nuclei Letters

, Volume 13, Issue 5, pp 704–707 | Cite as

Application of cluster analysis and autoregressive neural networks for the noise diagnostics of the IBR-2M reactor

  • Yu. N. Pepelyshev
  • Ts. Tsogtsaikhan
  • G. A. Ososkov
Computer Technologies in Physics

Abstract

The pattern recognition methodologies and artificial neural networks were used widely for the IBR-2M pulsed reactor noise diagnostics. The cluster analysis allows a detailed study of the structure and fast reactivity effects of IBR-2M and nonlinear autoregressive neural network (NAR) with local feedback connection allows predicting slow reactivity effects. In this work we present results of a study on pulse energy noise dynamics and prediction of liquid sodium flow rate through the core of the IBR-2M reactor using cluster analysis and an artificial neural network.

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Copyright information

© Pleiades Publishing, Ltd. 2016

Authors and Affiliations

  • Yu. N. Pepelyshev
    • 1
  • Ts. Tsogtsaikhan
    • 1
    • 2
  • G. A. Ososkov
    • 1
  1. 1.Joint Institute for Nuclear ResearchDubnaRussia
  2. 2.Institute of physics and technology, MASUlaanbaatarMongolia

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