Optimal Bridge Retrofitting Selection for Seismic Risk Management Using Genetic Algorithms and Neural Network–Based Surrogate Models-Reference-Cited by-同舟云学术

Optimal Bridge Retrofitting Selection for Seismic Risk Management Using Genetic Algorithms and Neural Network–Based Surrogate Models

Published:2023-12 Issue:4 Volume:29 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Silva-Lopez Rodrigo¹^ORCID,Baker Jack W.²

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Stanford Univ., Stanford, CA 94305 (corresponding author). ORCID: .

2. Professor, Dept. of Civil and Environmental Engineering, Stanford Univ., Stanford, CA 94305.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JITSE4.ISENG-2257

Reference51 articles.

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3. Bagley, J. D. 1967. The behavior of adaptive systems which employ genetic and correlation algorithms. Ann Arbor, MI: Univ. of Michigan.

4. Balmer M. N. Cetin K. Nagel and B. Raney. 2004. “Towards truly agent-based traffic and mobility simulations.” In Proc. 3rd Int. Joint Conf. on Autonomous Agents and Multiagent Systems 60–67. New York: IEEE.

5. Traffic assignment by paired alternative segments

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