Deep Reinforcement Learning–Enabled Bridge Management Considering Asset and Network Risks-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning–Enabled Bridge Management Considering Asset and Network Risks

Published:2022-09 Issue:3 Volume:28 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Yang David Y.¹^ORCID

Affiliation:

1. Assistant Professor, Dept. of Civil and Environmental Engineering, Portland State Univ., 1930 SW 4th Ave., Portland, OR 97201. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000704

Reference54 articles.

1. AASHTO. 2018. AASHTO transportation asset management guide. Washington, DC: AASHTO.

2. AASHTO. 2019. AASHTO manual for bridge element inspection. Washington, DC: AASHTO.

3. AASHTO. 2021. “AASHTOWare bridge management.” Accessed November 20 2021. https://www.aashtowarebridge.com.

4. Abadi M. et al. 2015. “TensorFlow: Large-scale machine learning on heterogeneous systems.” Accessed December 31 2019. https://www.tensorflow.org/.

5. A road infrastructure asset management process: gains in efficiency and effectiveness

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