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dc.contributor.authorPettersson, Klas
dc.contributor.authorKarzhou, Andrei
dc.contributor.authorPettersson, Irina
dc.date.accessioned2022-11-21T13:17:11Z
dc.date.available2022-11-21T13:17:11Z
dc.date.issued2022-02-22
dc.description.abstractThe Helmholtz equation has been used for modeling the sound pressure field under a harmonic load. Computing harmonic sound pressure fields by means of solving Helmholtz equation can quickly become unfeasible if one wants to study many different geometries for ranges of frequencies. We propose a machine learning approach, namely a feedforward dense neural network, for computing the average sound pressure over a frequency range. The data are generated with finite elements, by numerically computing the response of the average sound pressure, by an eigenmode decomposition of the pressure. We analyze the accuracy of the approximation and determine how much training data is needed in order to reach a certain accuracy in the predictions of the average pressure response.en_US
dc.identifier.citationPettersson, Karzhou, Pettersson. A Feedforward Neural Network for Modeling of Average Pressure Frequency Response. Acoustics Australia. 2022en_US
dc.identifier.cristinIDFRIDAID 2026641
dc.identifier.doi10.1007/s40857-021-00259-w
dc.identifier.issn0814-6039
dc.identifier.issn1839-2571
dc.identifier.urihttps://hdl.handle.net/10037/27449
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.ispartofKarzhou, A. (2023). Acoustical properties of solid-liquid composites and related computational problems. (Doctoral thesis). <a href=https://hdl.handle.net/10037/29410>https://hdl.handle.net/10037/29410</a>.
dc.relation.journalAcoustics Australia
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleA Feedforward Neural Network for Modeling of Average Pressure Frequency Responseen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)