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National Chung Hsing University Institutional Repository - NCHUIR > 農業暨自然資源學院 > 生物產業管理學系 > 依資料類型分類 > 期刊論文 >  Estimating the sound absorption coefficients of perforated wooden panels by using artificial neural networks

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/131242

標題: Estimating the sound absorption coefficients of perforated wooden panels by using artificial neural networks
作者: Lin, M.D.;Tsai, K.T.;Su, B.S.
關鍵字: Perforated wooden panel;Sound absorption coefficients;Artificial;neural network;Multiple linear regression;prediction;dynamics;systems
日期: 2009
Issue Date: 2012-12-07 16:20:51 (UTC+8)
關連: 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.
Relation: Applied Acoustics
Appears in Collections:[依資料類型分類] 期刊論文
[依教師分類] 蔡岡廷
[依教師分類] 林明德

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