Modeling of Construction Noise for Environmental Impact Assessment

Hamoda, Mohamed F. (2008) Modeling of Construction Noise for Environmental Impact Assessment. Journal of Construction in Developing Countries , 13 (1). pp. 79-89. ISSN 1823-6499

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This study measured the noise levels generated at different construction sites in reference to the stage of construction and the equipment used, and examined the methods to predict such noise in order to assess the environmental impact of noise. It included 33 construction sites in Kuwait and used artificial neural networks (ANNs) for the prediction of noise. A back-propagation neural network (BPNN) model was compared with a general regression neural network (GRNN) model. The results obtained indicated that the mean equivalent noise level was 78.7 dBA which exceeds the threshold limit. The GRNN model was superior to the BPNN model in its accuracy of predicting construction noise due to its ability to train quickly on sparse data sets. Over 93% of the predictions were within 5% of the observed values. The mean absolute error between the predicted and observed data was only 2 dBA. The ANN modeling proved to be a useful technique for noise predictions required in the assessment of environmental impact of construction activities.

Item Type: Article
Subjects: T Technology > TH Building construction > TH1-9745 Building construction
Divisions: Penerbit Universiti Sains Malaysia (USM Press) > Journal of Construction in Developing Countries
Depositing User: Mr Firdaus Mohamad
Date Deposited: 28 Sep 2018 09:06
Last Modified: 28 Sep 2018 09:06

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