Reinforcement Learning for Integrated Structural Control and Health Monitoring-Reference-Cited by-同舟云学术

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Reinforcement Learning for Integrated Structural Control and Health Monitoring

Published:2024-08 Issue:3 Volume:29 Page:
ISSN:1084-0680
Container-title:Practice Periodical on Structural Design and Construction
language:en
Short-container-title:Pract. Period. Struct. Des. Constr.

Author:

Javadinasab Hormozabad Sajad¹^ORCID,Jacobs Nathan²^ORCID,Gutierrez Soto Mariantonieta³^ORCID

Affiliation:

1. Ph.D. Candidate, Dept. of Civil Engineering, Univ. of Kentucky, 161 Raymond Building, Lexington, KY 40506. ORCID:

2. Professor, Dept. of Computer Science and Engineering, Washington Univ. in St. Louis, 1 Brookings Dr., St. Louis, MO 63130. ORCID:

3. Assistant Professor, School of Engineering Design and Innovation, Pennsylvania State Univ., 307 Engineering Design and Innovation Building, University Park, PA 16802 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/PPSCFX.SCENG-1455

Reference70 articles.

1. Reinforcement Learning for Structural Control

2. Structural Health Monitoring Techniques and Technologies for Large-Scale Structures: Challenges, Limitations, and Recommendations

3. Autonomous Unmanned Aerial Vehicle navigation using Reinforcement Learning: A systematic review

4. Bergstra, J., R. Bardenet, Y. Bengio, and B. Kégl. 2011. “Algorithms for hyper-parameter optimization.” In Advances in neural information processing systems, 24. Red Hook, NY: Curran Associates, Inc.

5. Simulations of a Variable Friction Device for Multihazard Mitigation

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