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Modeling of the Tonal Noise Characteristics in a Foil Flow by using Machine Learning

  • S. S. AbdurakipovEmail author
  • M. P. Tokarev
  • K. S. Pervunin
  • V. M. Dulin
Automation Systems in Scientific Research and Industry

Abstract

A machine learning approach for prediction the characteristics of tonal noise formed in a foil flow is tested. Experimental data are used to construct and analyze the mathematical models of pressure amplitude regression and models of classification of regimes of high-level tonal noise coming from the dimensionless parameters of the flow. Different families of algorithms are considered: from linear models to artificial neural networks. It is shown that a gradient boosting model with a determination coefficient 95% is the most accurate for describing and predicting the spectral curves of acoustic pressure on the entire interval of values of amplitudes and characteristic frequencies.

Keywords

machine learning foil flow tonal noise 

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Copyright information

© Allerton Press, Inc. 2019

Authors and Affiliations

  • S. S. Abdurakipov
    • 1
    • 2
    Email author
  • M. P. Tokarev
    • 1
    • 2
  • K. S. Pervunin
    • 1
    • 2
  • V. M. Dulin
    • 1
    • 2
  1. 1.Kutateladze Institute of Thermophysics, Siberian BranchRussian Academy of SciencesNovosibirskRussia
  2. 2.Novosibirsk State UniversityNovosibirskRussia

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