Mean-variance-validation technique for sequential kriging metamodels순차적 크리깅모델의 평균-분산 정확도 검증기법
- Other Titles
- 순차적 크리깅모델의 평균-분산 정확도 검증기법
- Authors
- Lee, Tae Hee; Kim, Hosung
- Issue Date
- May-2010
- Publisher
- 대한기계학회
- Keywords
- Accuracy; Cross validations; Kriging metamodel; Metamodel validation
- Citation
- Transactions of the Korean Society of Mechanical Engineers, A, v.34, no.5, pp.541 - 547
- Indexed
- SCOPUS
KCI
- Journal Title
- Transactions of the Korean Society of Mechanical Engineers, A
- Volume
- 34
- Number
- 5
- Start Page
- 541
- End Page
- 547
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/174987
- DOI
- 10.3795/KSME-A.2010.34.5.541
- ISSN
- 1226-4873
- Abstract
- The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean0 validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean0 validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.
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