Application of Machine Learning within an Asset Management Framework for Realizing the Impact of Trenching in Urban Environments-Reference-Cited by-同舟云学术

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Application of Machine Learning within an Asset Management Framework for Realizing the Impact of Trenching in Urban Environments

Published:2024-02-22 Issue: Volume:174 Page:464-474
ISSN:
Container-title:Geo-Congress 2024
language:
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Author:

Hojjati Aryan¹¹¹,Movahedifar Reza¹¹¹,Eskandari Torbaghan Mehran¹¹¹

Affiliation:

1. Dept. of Civil Engineering, School of Engineering, Univ. of Birmingham, Edgbaston, Birmingham, UK.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485347.047

Reference23 articles.

1. AIA (Asphalt Industry Alliance). (2022). Annual Local Authority Road Maintenance (ALARM) Asphalt Industry Alliance, Bristol, UK.

2. BSI (British Standards Institution). (2014). Code of practice for noise and vibration control on construction and open sites – Part 2: Vibration, BSI Standards Publication, London, UK.

3. “Identifying the most suitable machine learning approach for a road digital twin;Chen K.;Smart Infrastructure and Construction,2022

4. Quantifying damage from utility cuts in asphalt Pavement by using San Francisco’s Pavement Management data;Chow C.;Transportation Research Record: Journal of the Transportation Research Board,1999

5. Crown. (2021). Managing delay on the strategic road network. National Highways, Guildford, UK.

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