Pointwise ensemble of meta-models using v nearest points cross-validation
- Title
- Pointwise ensemble of meta-models using v nearest points cross-validation
- Author
- 최동훈
- Keywords
- Pointwise ensemble of meta-models; v nearest points cross validation; Meta-model
- Issue Date
- 2014-03
- Publisher
- Springer Science + Business Media
- Citation
- Structural and multidisciplinary optimization, Vol.50 No.3 [2014], pp. 383-394
- Abstract
- As the use of meta-models to replace computationally-intensive simulations for estimating real system behaviors increases, there is an increasing need to select appropriate meta-models that well represent real system behaviors. Since in most cases designers do not know the behavior of the real system a priori, however, they often have trouble selecting a suitable meta-model. In order to provide robust prediction performance, ensembles of meta-models have been developed which linearly combines stand-alone meta-models. In this study, we propose a new pointwise ensemble of meta-models whose weights vary according to the prediction point of interest. The suggested method can include all kinds of stand-alone meta-models for ensemble construction, and can interpolate real system response values at training points, even if regression models are included as stand-alone meta-models. To evaluate the effectiveness of the proposed method, its prediction performance is compared with those of existing ensembles of meta-models using well-known mathematical functions. The results show that our pointwise ensemble of meta-models provides more robust and accurate predictions than existing models for a majority of test problems. ⓒ 2014 Springer-Verlag Berlin Heidelberg.
- URI
- http://link.springer.com/article/10.1007%2Fs00158-014-1067-1http://hdl.handle.net/20.500.11754/50525
- ISSN
- 1615-147X
- DOI
- 10.1007/s00158-014-1067-1
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > MECHANICAL ENGINEERING(기계공학부) > Articles
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