Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference

•This paper proposes an improved Jaya algorithm for damage identification.•Objective function is improved based on sparse regularization and Bayesian inference.•Benchmark studies are conducted to demonstrate the improvement of this approach.•Numerical and experimental investigations are conducted to...

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Vydáno v:	Mechanical systems and signal processing Ročník 132; s. 211 - 231
Hlavní autoři:	Ding, Zhenghao, Li, Jun, Hao, Hong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin Elsevier Ltd 01.10.2019 Elsevier BV
Témata:	Algorithms Bayesian analysis Bayesian interference Clustering Concrete bridges Damage detection Global optimization Heuristic methods Identification Improved Jaya algorithm Mathematical models Measurement noise Modal data Noise measurement Optimization techniques Parameter identification Regularization Reinforced concrete Robustness (mathematics) Sparse regularization Statistical inference Structural damage Structural damage identification Uncertainty Structural damage identification Bayesian interference Measurement noise Uncertainty Sparse regularization Improved Jaya algorithm
ISSN:	0888-3270, 1096-1216
On-line přístup:	Získat plný text
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