Cited by 22Structural Health Monitoring TechniquesControl Systems and IdentificationMetaheuristic Optimization Algorithms Research

Simultaneous identification of structural damage and nonlinear hysteresis parameters by an evolutionary algorithm-based artificial neural network

Ding, Zhenghao, Li, Jun, Hao, Hong·2022·International Journal of Non-Linear Mechanics

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Crossref · 10.1016/j.ijnonlinmec.2022.103970

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Authors
Ding, Z., Li, J., & Hao, H.
Affiliations
  • Hong Kong Polytechnic University (HK)
  • Curtin University (AU)
Corresponding author
Li, Jun
Venue
International Journal of Non-Linear Mechanics
Publisher
Elsevier BV
Published
2022-06
Volume
142
Pages
103970
ISSN
0020-7462 (ISSN-L)
OpenAlex
W4212926153
Cited by
22
References
42
Citations by year
2026: 1 · 2025: 4 · 2024: 9 · 2023: 4 · 2022: 4
FWCI
2.36
Type
journal article
Language
en
Open access
closed
Locations
International Journal of Non-Linear Mechanics (publishedVersion)
Funders
  • China Scholarship Council (CSC 201606380106)
  • Curtin University of Technology
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
  • Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
  • Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
Keywords
structural damage detection, evolutionary algorithms, artificial neural networks, principal component analysis, dimensionality reduction, accelerometer data, vanishing and exploding gradients, local minima, structural health monitoring

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