title: A sequential optimization sampling method for metamodels with radial basis functions.
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.
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Guang
authors.initials: G
authors.lastname: Pan
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Pengcheng
authors.initials: P
authors.lastname: Ye
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Peng
authors.identifier: 0000-0002-8745-320X
authors.initials: P
authors.lastname: Wang
authors.affiliation: School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.
authors.forename: Zhidong
authors.initials: Z
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical