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BuHamdan, S, Alwisy, A, Bouferguene, A and Al-Hussein, M (2019) Novel Approach to Overcoming Discontinuity in Knowledge: Application in Value-Adding Frameworks in Construction Industry. Journal of Construction Engineering and Management, 145(08).

Duncheva, T and Bradley, F F (2019) Multifaceted Productivity Comparison of Off-Site Timber Manufacturing Strategies in Mainland Europe and the United Kingdom. Journal of Construction Engineering and Management, 145(08).

Hu, X, Chong, H, Wang, X and London, K (2019) Understanding Stakeholders in Off-Site Manufacturing: A Literature Review. Journal of Construction Engineering and Management, 145(08).

Jin, R, Zuo, J and Jong, J (2019) Scientometric Review of Articles Published in ASCE’s Journal of Construction Engineering and Management from 2000 to 2018. Journal of Construction Engineering and Management, 145(08), 06019001.

Kwon, N, Cho, J, Lee, H, Yoon, I and Park, M (2019) Compensation Cost Estimation Model for Construction Noise Claims Using Case-Based Reasoning. Journal of Construction Engineering and Management, 145(08).

  • Type: Journal Article
  • Keywords: Noise management; Compensation estimation; Noise-related problems; Case-based reasoning; Preconstruction phase;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001675
  • Abstract:
    Noise due to construction is recognized as a crucial source of harm to the surroundings of a site. A number of noise-related problems can cause significant risk to an ongoing project. As a first step toward coping with noise, this paper presents a model developed for estimating the noise-related compensation cost through case-based reasoning (CBR). An experiment was performed with 20 randomly selected test cases. The compensation costs were estimated based on damage days and excessive noise level of similar cases. A Monte Carlo simulation (MCS) was adopted to deal with limited and uncertain data. The results showed that the cases had a similarity of 91.8% on average, and the mean absolute error ratio (MAER) of the estimated cost based on data revised by MCS was approximately 11.8%. This indicates that the estimated and actual costs were similar, which validates the applicability of the model. This research contributes to the field of construction noise management by providing environmental managers with a systematic approach for estimating noise-related compensation during the preconstruction phase.

Le, C, Le, T, Jeong, H D and Lee, E (2019) Geographic Information System–Based Framework for Estimating and Visualizing Unit Prices of Highway Work Items. Journal of Construction Engineering and Management, 145(08).

Qiao, Y, Fricker, J D and Labi, S (2019) Influence of Project Bundling on Maintenance of Traffic Costs across Highway Project Types. Journal of Construction Engineering and Management, 145(08).

Seyis, S (2019) Pros and Cons of Using Building Information Modeling in the AEC Industry. Journal of Construction Engineering and Management, 145(08).