Adaptive virtual support vector machine for reliability analysis of high-dimensional problems

DOI10.1007/S00158-012-0857-6zbMath1274.62429OpenAlexW2084625646MaRDI QIDQ381967

Mohammad Hasan, H. S. Yoon

Publication date: 15 November 2013

Published in: Structural and Multidisciplinary Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00158-012-0857-6

zbMATH Keywords

sequential samplingsurrogate modelsupport vector machine (SVM)\texttt{SURROGATES toolbox}\texttt{SVM and Kernel Methods Matlab Toolbox}high-dimensional problemvirtual samplesvirtual support vector machine (VSVM)

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Reliability and life testing (62N05)

Related Items (6)

Improved reliability-based optimization with support vector machines and its application in aircraft wing design ⋮ A new active-learning estimation method for the failure probability of structural reliability based on kriging model and simple penalty function ⋮ SS-MASVM: an advanced technique for assessing failure probability of high-dimensional complex systems using the multi-class adaptive support vector machine ⋮ A novel nested stochastic Kriging model for response noise quantification and reliability analysis ⋮ Efficient structural reliability analysis based on adaptive Bayesian support vector regression ⋮ Modified screening-based kriging method with cross validation and application to engineering design

Uses Software

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• LIBSVM
• SURROGATES
• SVM

Cites Work

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