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


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.


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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