Haiyang Hu, Zhansi Jiang, Yanxue Wang, Shuilong He
{"title":"A multi-criteria adaptive sequential sampling method for radial basis function","authors":"Haiyang Hu, Zhansi Jiang, Yanxue Wang, Shuilong He","doi":"10.1504/ijcsm.2020.10029254","DOIUrl":null,"url":null,"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.","PeriodicalId":399731,"journal":{"name":"Int. J. Comput. Sci. Math.","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Sci. Math.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijcsm.2020.10029254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.