請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/49490
標題: Estimating the sound absorption coefficients of perforated wooden panels by using artificial neural networks
作者: Lin, M.D.
林明德
Tsai, K.T.
Su, B.S.
蔡岡廷
關鍵字: Perforated wooden panel
Sound absorption coefficients
Artificial
neural network
Multiple linear regression
prediction
dynamics
systems
期刊/報告no:: Applied Acoustics, Volume 70, Issue 1, Page(s) 31-40.
摘要: Developing efficient sound absorption materials is a relevant topic for large scale structures such as gymnasiums, shopping malls, airports and stations. This study employs artificial neural network (ANN) algorithm to estimate the sound absorption coefficients of different perforated wooden panels with various setting combinations including perforation percentage, backing material and thickness. The training data sets are built by carrying out a series of experimental measurements in the reverberation room to evaluate the sound absorption characteristics of perforated wooden panels. A multiple linear regression (MLR) model is also developed for making comparisons with ANN. The analytical results indicate that the ANN exhibits satisfactory reliability of a correlation between estimation and truly measured absorption coefficients of approximately 0.85. However, MLR cannot be applied to nonlinear cases. ANN is a useful and reliable tool for estimating sound absorption coefficients estimation. (C) 2008 Elsevier Ltd. All rights reserved.
URI: http://hdl.handle.net/11455/49490
ISSN: 0003-682X
文章連結: http://dx.doi.org/10.1016/j.apacoust.2008.02.001
顯示於類別:生物產業管理學系

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