A machine learning ensemble model for predicting pavement conditions using automatic laser crack measurement data-Reference-Cited by-同舟云学术

A machine learning ensemble model for predicting pavement conditions using automatic laser crack measurement data

Published:2023-04-06 Issue:1 Volume:24 Page:
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Bai Lihui¹,Zhang Jie²,Zhu Xuwen³,Alam Md Morshedul¹,Sun Zhihui⁴

Affiliation:

1. Department of Industrial Engineering, University of Louisville, Louisville, KY, USA

2. FedEx Corporation, Memphis, TN, USA

3. Department of Information Systems, Statistics and Management Science, University of Alabama, Tuscaloosa, AL, USA

4. Department of Civil and Environmental Engineering, University of Louisville, Louisville, KY, USA

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2023.2188591

Reference31 articles.

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2. Performance evaluation of sensor-and image-based technologies for automated pavement condition surveys;Capuruço R. A. C.;Transportation Research Record: Journal of the Transportation Research Board,1968

3. Fully Automated Road Defect Detection Using Street View Images

4. Chan S. Sc M. A. and Eng P. 2016. Transition from manual to automated pavement distress data collection and performance modelling in the pavement management system. In TAC 2016: Efficient Transportation-Managing the Demand-2016 Conference and Exhibition of the Transportation Association of Canada .

5. Combining forecasts: A review and annotated bibliography

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