Development of noise emission database from construction site equipments for construction noise prediction

Development of noise emission database from construction site equipments for construction noise prediction

The paper described the need to establish noise emission database for equipment of local construction. The strategic framework that is advocated by this study was highlighted. The proposed database can help to curb underestimated or overestimated sound pressure level prediction during planning stage...

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Main Authors: H., Mohd. Noh, Z., Haron, K., Yahya
Format: Conference or Workshop Item
Published: 2009
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utm.my/id/eprint/15063/
http://proceeding.eacef.com/ojs/index.php/EACEF/article/view/178/139
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Institution: Universiti Teknologi Malaysia
id my.utm.15063
record_format eprints
spelling my.utm.150632020-07-20T01:23:59Z http://eprints.utm.my/id/eprint/15063/ Development of noise emission database from construction site equipments for construction noise prediction H., Mohd. Noh Z., Haron K., Yahya TA Engineering (General). Civil engineering (General) The paper described the need to establish noise emission database for equipment of local construction. The strategic framework that is advocated by this study was highlighted. The proposed database can help to curb underestimated or overestimated sound pressure level prediction during planning stage and consequently can address the annoyance sufficiently and could be used by consultant or environmental engineers in predicting the noise exposure. 2009 Conference or Workshop Item PeerReviewed H., Mohd. Noh and Z., Haron and K., Yahya (2009) Development of noise emission database from construction site equipments for construction noise prediction. In: Joint Conference of 7th Asia Pacific Structural Engineering and Construction Conference 2009 (APSEC2009) and 2nd European Asian Civil Engineering Forum (EACEF 2009), 2009, Awana Porto Malai, Langkawi, Malaysia. http://proceeding.eacef.com/ojs/index.php/EACEF/article/view/178/139
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
H., Mohd. Noh
Z., Haron
K., Yahya
Development of noise emission database from construction site equipments for construction noise prediction
description The paper described the need to establish noise emission database for equipment of local construction. The strategic framework that is advocated by this study was highlighted. The proposed database can help to curb underestimated or overestimated sound pressure level prediction during planning stage and consequently can address the annoyance sufficiently and could be used by consultant or environmental engineers in predicting the noise exposure.
format Conference or Workshop Item
author H., Mohd. Noh
Z., Haron
K., Yahya
author_facet H., Mohd. Noh
Z., Haron
K., Yahya
author_sort H., Mohd. Noh
title Development of noise emission database from construction site equipments for construction noise prediction
title_short Development of noise emission database from construction site equipments for construction noise prediction
title_full Development of noise emission database from construction site equipments for construction noise prediction
title_fullStr Development of noise emission database from construction site equipments for construction noise prediction
title_full_unstemmed Development of noise emission database from construction site equipments for construction noise prediction
title_sort development of noise emission database from construction site equipments for construction noise prediction
publishDate 2009
url http://eprints.utm.my/id/eprint/15063/
http://proceeding.eacef.com/ojs/index.php/EACEF/article/view/178/139
_version_ 1674066111464734720

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