A Decision-Making Framework for Load Rating Planning of Aging Bridges Using Deep Reinforcement Learning-Reference-Cited by-同舟云学术

A Decision-Making Framework for Load Rating Planning of Aging Bridges Using Deep Reinforcement Learning

Published:2021-11 Issue:6 Volume:35 Page:04021024
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Cheng Minghui¹,Frangopol Dan M.²

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015.

2. Professor and Fazlur R. Khan Endowed Chair of Structural Engineering and Architecture, Dept. of Civil and Environmental Engineering, ATLSS Engineering Research Center, Lehigh Univ., 117 ATLSS Dr., Bethlehem, PA 18015 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000991

Reference62 articles.

1. AASHTO. 2017. AASHTO LRFD bridge design specifications. Washington, DC: AASHTO.

2. AASHTO. 2018. The manual for bridge evaluation. Washington, DC: AASHTO.

3. Rating and Reliability of Existing Bridges in a Network

4. Computational Platform for Predicting Lifetime System Reliability Profiles for Different Structure Types in a Network

5. Bridge Load Testing: State-of-the-Practice

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