An improved adaptive sampling scheme for the construction of explicit boundaries
| Autor: | Anirban Basudhar, Samy Missoum |
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| Rok vydání: | 2010 |
| Předmět: |
Scheme (programming language)
Mathematical optimization Control and Optimization Adaptive sampling Sample (statistics) Computer Graphics and Computer-Aided Design Computer Science Applications Support vector machine Control and Systems Engineering Kernel (statistics) Convergence (routing) Limit state design Engineering design process computer Algorithm Software Mathematics computer.programming_language |
| Zdroj: | Structural and Multidisciplinary Optimization. 42:517-529 |
| ISSN: | 1615-1488 1615-147X |
| DOI: | 10.1007/s00158-010-0511-0 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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