Model error effects in supervised damage identification of structures with numerically trained classifiers-Reference-Cited by-同舟云学术

Model error effects in supervised damage identification of structures with numerically trained classifiers

Published:2023-02 Issue: Volume:184 Page:109741
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Seventekidis Panagiotis,Giagopoulos Dimitrios

Funder

GSRT

European Regional Development Fund

European Commission

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference52 articles.

1. Validation of vibration-based structural health monitoring on retrofitted railway bridge KW51;Maes;Mech. Syst. Sig. Process.,2022

2. Eloi Figueiredo, James Brownjohn, Three decades of statistical pattern recognition paradigm for SHM of bridges, Structural Health Monitoring, Volume 0, 2022, p: 1–37.

3. Sandeep Sony, Sunanda Gamage, Ayan Sadhu, Jagath Samarabandu, Vibration-based multiclass damage detection and localization using long short-term memory networks, Structures, Volume 35, 2022, p: 436-451.

4. Unsupervised learning-based damage assessment of full-scale civil structures under long-term and short-term monitoring;Daneshvar;Eng. Struct.,2022

5. State-of-the-art review on advancements of data mining in structural health monitoring;Gordan;Measurement,2022

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