A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions
Joint Authors
Wang, Peng
Pan, Guang
Ye, Pengcheng
Yang, Zhidong
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-15
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs.
The accuracy of metamodels is strongly affected by the sampling methods.
In this paper, a new sequential optimization sampling method is proposed.
Based on the new sampling method, metamodels can be constructed repeatedly through the addition of sampling points, namely, extrema points of metamodels and minimum points of density function.
Afterwards, the more accurate metamodels would be constructed by the procedure above.
The validity and effectiveness of proposed sampling method are examined by studying typical numerical examples.
American Psychological Association (APA)
Pan, Guang& Ye, Pengcheng& Wang, Peng& Yang, Zhidong. 2014. A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1048671
Modern Language Association (MLA)
Pan, Guang…[et al.]. A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions. The Scientific World Journal No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-1048671
American Medical Association (AMA)
Pan, Guang& Ye, Pengcheng& Wang, Peng& Yang, Zhidong. A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1048671
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048671