A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions. (15th July 2014)

• Record Type: Journal Article
• Authors: Pan, Guang; Ye, Pengcheng; Wang, Peng; Yang, Zhidong
• Other Names: Zhou Huamin Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2014(2014)
• Publication Date: 2014-07-15
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2014/192862
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : 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.