Bridge Infrastructure Asset Management System: Comparative Computational Machine Learning Approach for Evaluating and Predicting Deck Deterioration Conditions-Reference-Cited by-同舟云学术

Bridge Infrastructure Asset Management System: Comparative Computational Machine Learning Approach for Evaluating and Predicting Deck Deterioration Conditions

Published:2020-09 Issue:3 Volume:26 Page:04020032
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Assaad Rayan¹,El-adaway Islam H.²^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil, Architectural, and Environmental Engineering, Missouri Univ. of Science and Technology, 218 Butler-Carlton Hall, 1401 N. Pine St., Rolla, MO 65409.

2. Hurst-McCarthy Professor of Construction Engineering and Management, Professor of Civil Engineering, and Founding Director of Missouri Consortium for Construction Innovation, Dept. of Civil, Architectural, and Environmental Engineering/Dept. of Engineering Management and Systems Engineering, Missouri Univ. of Science and Technology, 228 Butler-Carlton Hall, 1401 N. Pine St., Rolla, MO 65409 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000572

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3. Almaliki Z. 2019. “Do you know how to choose the right machine learning algorithm among 7 different types?” Accessed November 12 2019. https://towardsdatascience.com/do-you-know-how-to-choose-the-right-machine-learning-algorithm-among-7-different-types-295d0b0c7f60.

4. Structural description to recognizing hand-printed Arabic characters using decision tree learning techniques;Amin A.;Int. J. Comput. Appl.,2006

5. ARTBA (American Road and Transportation Builders Association). 2018. “2017 structurally deficient bridges ranked by total number of deficient bridges.” Accessed November 12 2018. https://www.artbabridgereport.org/.

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