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Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis

Acoustic noise; Noise pollution; Rapid transit; Wind; Mass rapid transit; MRT train; Noise levels; Non-operating hour; Operating hours; Prediction modelling; Regression modelling; Sound level meter; Stepwise regression analysis; Regression analysis

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Main Authors: Hamid N.B., Sanik M.E., Noor H.M., Prasetijo J., Mokhtar M., Azmi M.A.M., Yahaya M.I., Ramli M.Z.
Other Authors: 57190252816
Format: Conference Paper
Published: Springer Science and Business Media Deutschland GmbH 2023
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spelling my.uniten.dspace-271552023-05-29T17:40:17Z Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis Hamid N.B. Sanik M.E. Noor H.M. Prasetijo J. Mokhtar M. Azmi M.A.M. Yahaya M.I. Ramli M.Z. 57190252816 42561659300 57807815400 36562293000 57190069071 57221099934 57712384300 57195984780 Acoustic noise; Noise pollution; Rapid transit; Wind; Mass rapid transit; MRT train; Noise levels; Non-operating hour; Operating hours; Prediction modelling; Regression modelling; Sound level meter; Stepwise regression analysis; Regression analysis Nowadays, rail transport is one of the most important transport modes chosen by Malaysians. However, the noise pollution caused by the railway causes complaints from residents living near this track. Therefore, the operator needs to order their workers to conduct monthly observations and measurements of their train noise level in the selected area. The conventional method requires more time and energy as the number of areas to monitor is various and the sound level measurement tools used are also expensive. Thus, a study was carried out to determine the current noise level produced by MRT train in the residential areas near to the Pusat Bandar Damansara station. The noise level measurement was conducted at Lorong Kasah Tepi and Medan Damansara Carpark, which are located nearby the Sungai Buloh�Kajang MRT Line. The noise level was measured at each location with three different slope distances using a sound level meter during operating and non-operating hours. Other than that, MRT speed and wind speed were measured as predictors to develop the Mass Rapid Transit Noise prediction model using the stepwise regression analysis. From the analysis, 88.37% of variation in Mass Rapid Transit Noise can be explained by the regression model. � 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Final 2023-05-29T09:40:16Z 2023-05-29T09:40:16Z 2022 Conference Paper 10.1007/978-981-16-8903-1_33 2-s2.0-85134319357 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134319357&doi=10.1007%2f978-981-16-8903-1_33&partnerID=40&md5=5f19376ea20170ef19399f03319b58f6 https://irepository.uniten.edu.my/handle/123456789/27155 273 379 389 Springer Science and Business Media Deutschland GmbH Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Acoustic noise; Noise pollution; Rapid transit; Wind; Mass rapid transit; MRT train; Noise levels; Non-operating hour; Operating hours; Prediction modelling; Regression modelling; Sound level meter; Stepwise regression analysis; Regression analysis
author2 57190252816
author_facet 57190252816
Hamid N.B.
Sanik M.E.
Noor H.M.
Prasetijo J.
Mokhtar M.
Azmi M.A.M.
Yahaya M.I.
Ramli M.Z.
format Conference Paper
author Hamid N.B.
Sanik M.E.
Noor H.M.
Prasetijo J.
Mokhtar M.
Azmi M.A.M.
Yahaya M.I.
Ramli M.Z.
spellingShingle Hamid N.B.
Sanik M.E.
Noor H.M.
Prasetijo J.
Mokhtar M.
Azmi M.A.M.
Yahaya M.I.
Ramli M.Z.
Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
author_sort Hamid N.B.
title Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
title_short Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
title_full Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
title_fullStr Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
title_full_unstemmed Prediction Model of Mass Rapid Transit Noise Level Using the Stepwise Regression Analysis
title_sort prediction model of mass rapid transit noise level using the stepwise regression analysis
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2023
_version_ 1806426027012915200
score 13.211869

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