Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/140301
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dc.contributor.authorLiu, Haitaoen_US
dc.contributor.authorOng, Yew-Soonen_US
dc.contributor.authorCai, Jianfeien_US
dc.date.accessioned2020-05-28T01:09:32Z-
dc.date.available2020-05-28T01:09:32Z-
dc.date.issued2017-
dc.identifier.citationLiu, H., Ong, Y.-S, & Cai, J. (2018). A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design. Structural and Multidisciplinary Optimization, 57(1), 393-416. doi:10.1007/s00158-017-1739-8en_US
dc.identifier.issn1615-147Xen_US
dc.identifier.urihttps://hdl.handle.net/10356/140301-
dc.description.abstractMetamodeling is becoming a rather popular means to approximate the expensive simulations in today’s complex engineering design problems since accurate metamodels can bring in a lot of benefits. The metamodel accuracy, however, heavily depends on the locations of the observed points. Adaptive sampling, as its name suggests, places more points in regions of interest by learning the information from previous data and metamodels. Consequently, compared to traditional space-filling sampling approaches, adaptive sampling has great potential to build more accurate metamodels with fewer points (simulations), thereby gaining increasing attention and interest by both practitioners and academicians in various fields. Noticing that there is a lack of reviews on adaptive sampling for global metamodeling in the literature, which is needed, this article categorizes, reviews, and analyzes the state-of-the-art single−/multi-response adaptive sampling approaches for global metamodeling in support of simulation-based engineering design. In addition, we also review and discuss some important issues that affect the success of an adaptive sampling approach as well as providing brief remarks on adaptive sampling for other purposes. Last, challenges and future research directions are provided and discussed.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.language.isoenen_US
dc.relation.ispartofStructural and Multidisciplinary Optimizationen_US
dc.rights© 2017 Springer-Verlag GmbH Germany. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleA survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering designen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.contributor.organizationData Science and Artificial Intelligence Research Centeren_US
dc.contributor.organizationRolls-Royce@NTU Corporate Laboratoryen_US
dc.identifier.doi10.1007/s00158-017-1739-8-
dc.identifier.scopus2-s2.0-85021270054-
dc.identifier.issue1en_US
dc.identifier.volume57en_US
dc.identifier.spage393en_US
dc.identifier.epage416en_US
dc.subject.keywordsAdaptive Samplingen_US
dc.subject.keywordsGlobal Metamodelingen_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
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