Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1466
Title: Effect of error metrics on optimum weight factor selection for ensemble of metamodels
Authors: Acar, Erdem
143688
Keywords: Ensemble
Error metrics
Metamodeling
Surrogate modeling
Issue Date: 1-Apr-2015
Publisher: Pergamon-Elsevier Science Ltd
Source: Acar, E. (2015). Effect of error metrics on optimum weight factor selection for ensemble of metamodels. Expert Systems with Applications, 42(5), 2703-2709.
Abstract: Optimization of complex engineering systems is performed using computationally expensive high fidelity computer simulations (e.g., finite element analysis). During optimization these high-fidelity simulations are performed many times, so the computational cost becomes excessive. To alleviate the computational burden, metamodels are used to mimic the behavior of these computationally expensive simulations. The prediction capability of metamodeling can be improved by combining various types of models in the form of a weighted average ensemble. The contribution of each models is usually determined such that the root mean square cross validation error (RMSE-CV) is minimized in an aim to minimize the actual root mean square error (RMSE). However, for some applications, other error metrics such as the maximum absolute error (MAXE) may be the error metric of interest. It can be argued, intuitively, that when MAXE is more important than RMSE, the weight factors in ensemble should be determined by minimizing the maximum absolute cross validation error (MAXE-CV). Interestingly, it is found that the ensemble model based on MAXE-CV minimization is less accurate than the ensemble model based on RMSE-CV minimization even if the MAXE is the metric of interest. The reason is found to be that MAXE-CV is mostly related with the geography of the DOE rather than the prediction ability of metamodels. (C) 2014 Elsevier Ltd. All rights reserved.
URI: https://www.sciencedirect.com/science/article/pii/S0957417414007064
https://hdl.handle.net/20.500.11851/1466
ISSN: 0957-4174
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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