A novel mixed uncertainty support vector machine method for structural reliability analysis

DOI10.1007/s00707-020-02906-1zbMath1492.74142OpenAlexW3132102713MaRDI QIDQ2234195

Ling-Fei You, Shuang Zhou, Jie Wu, Jianguo Zhang

Publication date: 18 October 2021

Published in: Acta Mechanica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00707-020-02906-1

zbMATH Keywords

particle swarm optimization methodfuzzy uncertaintyrandom uncertaintyadvanced Yang distancefuzziness failure criterionrandom fuzzy mixed sampling points

Mathematics Subject Classification ID

Thin bodies, structures (74K99) Reliability and life testing (62N05) Numerical and other methods in solid mechanics (74S99) Stochastic and other probabilistic methods applied to problems in solid mechanics (74S60)

Related Items (1)

EMCS-SVR: hybrid efficient and accurate enhanced simulation approach coupled with adaptive SVR for structural reliability analysis

Cites Work

• Support vector machine for structural reliability analysis
• On a class of fuzzy \(c\)-numbers clustering procedures for fuzzy data
• Interval optimization based line sampling method for fuzzy and random reliability analysis
• Confidence bounds on component reliability in the presence of mixed uncertain variables
• Higher-order failure probability calculation using nonlinear approximations
• Unified uncertainty analysis under probabilistic, evidence, fuzzy and interval uncertainties
• Adaptive reliability analysis based on a support vector machine and its application to rock engineering
• Support vector regression based metamodeling for seismic reliability analysis of structures
• Convergence theorems for a class of simulated annealing algorithms on ℝ^d
• LEVEL FUZZY SETS
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