Assessment of traffic noise levels in urban areas using different soft computing techniques

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traf...

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Bibliographic Details
Published inThe Journal of the Acoustical Society of America Vol. 140; no. 4; pp. EL340 - EL345
Main Authors Tomić, J., Bogojević, N., Pljakić, M., Šumarac-Pavlović, D.
Format Journal Article
LanguageEnglish
Published United States 01.10.2016
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Summary:Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.4964786