Robust estimation of support vector regression via residual bootstrap adoption

Title
Robust estimation of support vector regression via residual bootstrap adoption
Authors
최동훈
Keywords
Support vector regression; Bootstrap; Residual; Root median square error
Issue Date
2015-01
Publisher
KOREAN SOC MECHANICAL ENGINEERS
Citation
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, v. 29, NO 1, Page. 279-289
Abstract
As current system designs grow increasingly complex and expensive to analyze, the need for design optimization has also grown. In this study, a more stable approximation model is proposed via the application of a bootstrap to support vector regression (SVR). SVR expresses the nonlinearity of the system relatively well. However, using SVR does not always guarantee accurate results because it is sensitive to the input parameters. To overcome this drawback, we apply a bootstrap to SVR, using the residual from SVR as the bootstrap. The performance of the proposed method is evaluated via application to numerical examples and a real problem. We observed that the proposed method not only produced valuable results but also noticeably eliminated the negative effects of input parameters.
URI
http://hdl.handle.net/20.500.11754/21472https://link.springer.com/article/10.1007%2Fs12206-014-1234-8
ISSN
1738-494X
DOI
http://dx.doi.org/10.1007/s12206-014-1234-8
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > MECHANICAL ENGINEERING(기계공학부) > Articles
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