Improving Culvert Condition Prediction Models Using Federated Learning: The Case Study of Utah-Reference-Cited by-同舟云学术

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Improving Culvert Condition Prediction Models Using Federated Learning: The Case Study of Utah

Published:2024-03-18 Issue: Volume:2675 Page:359-368
ISSN:
Container-title:Construction Research Congress 2024
language:
Short-container-title:

Author:

Mohammadi Pouria¹²³,Rashidi Abbas¹²³,Asgari Sadegh¹²³

Affiliation:

1. Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT. ORCID: .

2. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Utah, Salt Lake City, UT.

3. Associate Professor, Dept. of Civil Engineering, Merrimack College, North Andover, MA.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485262.037

Reference20 articles.

1. Act C. C. P. 2018. “CCPA.” Accessed April 22 2023. https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5.

2. Beutel, D. J., et al. 2020. Flower: A Friendly Federated Learning Research Framework.

3. Highway asset and pavement condition management using mobile photogrammetry;Farhadmanesh M.;Transp. Res. Rec,2021

4. The use of decision tree based predictive models for improving the culvert inspection process;Gao C.;Adv. Eng. Informatics,2021

5. Machine Learning Algorithms for Construction Projects Delay Risk Prediction

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