A data-driven force-thermal coupling load identification method considering multi-source uncertainties of structural characteristics and measuring noises

DOI10.1016/J.CMA.2024.116937MaRDI QIDQ6497176

Lei Wang, Di Wu, Unnamed Author, Unnamed Author

Publication date: 6 May 2024

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

uncertaintyartificial neural networksparticle swarm optimizationload identificationforce-thermal coupling

Mathematics Subject Classification ID

Mechanics of deformable solids (74-XX) Systems theory; control (93-XX)

Cites Work

• Antioptimization of structures with large uncertain-but-non-random parameters via interval analysis
• A radial basis function artificial neural network (RBF ANN) based method for uncertain distributed force reconstruction considering signal noises and material dispersion
• A WAVELET-BASED APPROACH FOR THE IDENTIFICATION OF LINEAR TIME-VARYING DYNAMICAL SYSTEMS
• Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data
• The inverse determination of aerodynamic loading from structural response data using neural networks
• A logical calculus of the ideas immanent in nervous activity

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