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Structural and Multidisciplinary Optimization

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01.10.2010 | Research Paper

An improved adaptive sampling scheme for the construction of explicit boundaries

verfasst von: Anirban Basudhar, Samy Missoum

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 4/2010

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Abstract

This article presents an improved adaptive sampling scheme for the construction of explicit decision functions (constraints or limit state functions) using Support Vector Machines (SVMs). The proposed work presents substantial modifications to an earlier version of the scheme (Basudhar and Missoum, Comput Struct 86(19–20):1904–1917, 2008). The improvements consist of a different choice of samples, a more rigorous convergence criterion, and a new technique to select the SVM kernel parameters. Of particular interest is the choice of a new sample chosen to remove the “locking” of the SVM, a phenomenon that was not understood in the previous version of the algorithm. The new scheme is demonstrated on analytical problems of up to seven dimensions.

Vorheriger Artikel Topology optimization of flexible micro-fluidic devices

Nächster Artikel Optimal design of box-section sandwich beams subject to moving load

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Titel: An improved adaptive sampling scheme for the construction of explicit boundaries
verfasst von: Anirban Basudhar
Samy Missoum
Publikationsdatum: 01.10.2010
Verlag: Springer-Verlag
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 4/2010
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-010-0511-0

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