Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks

Garg, N.; Dhruw, S.; Gandhi, L.

doi:10.1515/aoa-2017-0068

Artykuł - szczegóły

Tytuł artykułu

Prediction of Sound Insulation of Sandwich Partition Panels by Means of Artificial Neural Networks

Autorzy

Garg N. , Dhruw S. , Gandhi L.

Treść / Zawartość

Pełne teksty:

Garg_Prediction of Sound Insulation_4_2017.pdf

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Identyfikatory

DOI

10.1515/aoa-2017-0068

Warianty tytułu

Języki publikacji

Abstrakty

The paper presents the application of Artificial Neural Networks (ANN) in predicting sound insulation through multi-layered sandwich gypsum partition panels. The objective of the work is to develop an Artificial Neural Network (ANN) model to estimate the R_w and STC value of sandwich gypsum constructions. The experimental results reported by National Research Council, Canada for Gypsum board walls (Halliwell et al., 1998) were utilized to develop the model. A multilayer feed-forward approach comprising of 13 input parameters was developed for predicting the R_w and STC value of sandwich gypsum constructions. The Levenberg-Marquardt optimization technique has been used to update the weights in back-propagation algorithm. The presented approach could be very useful for design and optimization of acoustic performance of new sandwich partition panels providing higher sound insulation. The developed ANN model shows a prediction error of ± 3 dB or points with a confidence level higher than 95%.

Słowa kluczowe

weighted sound reduction index Rw Sound Transmission Class STC

Wydawca

Instytut Podstawowych Problemów Techniki PAN
Komitet Akustyki PAN
Polskie Towarzystwo Akustyczne

Czasopismo

Archives of Acoustics

Rocznik

2017

Tom

Vol. 42, No. 4

Strony

643--651

Opis fizyczny

Bibliogr. 60 poz., rys., tab., wykr.

Twórcy

autor

Garg N.

ngarg@nplindia.org

CSIR-National Physical Laboratory, New Delhi – 110012, India

autor

Dhruw S.

National Institute of Technology, Hamirpur, 1601 Hamirpur – 177 005, India

autor

Gandhi L.

National Institute of Technology, Kurukshetra, Kurukshetra – 136 119, India

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-45698699-ba7b-4bca-b037-f32733d23cce