Development of a prediction model for the proportion of buildings exposed to construction noise in excess of the construction noise regulation at urban construction sites

Juwon Hong, Hyuna Kang, Taehoon Hong, Hyo Seon Park, Dong Eun Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Noise in construction projects, one of the major problems at urban construction sites, should be evaluated and managed according to the construction noise regulation. This study developed a prediction model for proportion of buildings exposed to noise in excess of the construction noise regulation (the overexposed building ratio) as the evaluation index, to effectively manage construction noise using elastic net linear regression and polynomial interpolation. Through the conducted case study, the developed prediction model showed better prediction performance (a 35.5% average increase) than the general model. The developed prediction model was applicable to construction sites with no database and was able to predict not only the overexposed building ratio but also the number of dwellers exposed to such noise level. The prediction model can encourage construction companies and dwellers to actively participate in the management of construction noise and can provide acoustic comfort to communities.

Original languageEnglish
Article number103656
JournalAutomation in Construction
Volume125
DOIs
Publication statusPublished - 2021 May

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grand funded by the Korea Government (MSIT; Ministry of Science and ICT) (NRF-2018R1A5A1025137).

Publisher Copyright:
© 2021 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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