A multi-criteria adaptive sequential sampling method for radial basis function. (5th May 2020)

• Record Type: Journal Article
• Authors: Hu, Haiyang; Jiang, Zhansi; Wang, Yanxue; He, Shuilong
• Is Part Of: International journal of computing science and mathematics. Volume 11:Number 4(2020)
• Page Start: 305
• Page End: 315
• Publication Date: 2020-05-05
• Subjects: multi-criteria adaptive sequential sampling -- global approximation -- metamodel -- radial basis function; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

A multi-criteria adaptive sequential sampling method is proposed for radial basis function metamodel and a new global approximation method is developed in this paper. In this new sampling method, objective, curvature and distance are considered as sampling criteria. With the three criteria, it guarantees that the entire domain will be covered by samples, and more sampling points will be gathered in the peak and valley regions, which is useful for enhance accuracy and efficiency of approximation model. Intensive testing shows that the efficiency of method and accuracy of metamodel are satisfactory by this new global approximation method.