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

Результат исследования: Научные публикации в периодических изданияхстатья

2 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаанглийский
Страницы (с-по)205-211
Число страниц7
ЖурналOptoelectronics, Instrumentation and Data Processing
Том55
Номер выпуска2
DOI
СостояниеОпубликовано - 1 мар 2019

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