Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/328046
Type: Artigo
Title: Ensemble Of Metamodels: The Augmented Least Squares Approach
Author: Ferreira
Wallace G.; Serpa
Alberto L.
Abstract: In this work we present an approach to create ensemble of metamodels (or weighted averaged surrogates) based on least squares (LS) approximation. The LS approach is appealing since it is possible to estimate the ensemble weights without using any explicit error metrics as in most of the existent ensemble methods. As an additional feature, the LS based ensemble of metamodels has a prediction variance function that enables the extension to the efficient global optimization. The proposed LS approach is a variation of the standard LS regression by augmenting the matrices in such a way that minimizes the effects of multicollinearity inherent to calculation of the ensemble weights. We tested and compared the augmented LS approach with different LS variants and also with existent ensemble methods, by means of analytical and real-world functions from two to forty-four variables. The augmented least squares approach performed with good accuracy and stability for prediction purposes, in the same level of other ensemble methods and has computational cost comparable to the faster ones.
Subject: Ensemble Of Metamodels
Weighted Average Surrogates
Least Squares Approximation
Editor: Springer
New York
Citation: Structural And Multidisciplinary Optimization. Springer, v. 53, p. 1019 - 1046, 2016.
Rights: fechado
Identifier DOI: 10.1007/s00158-015-1366-1
Address: https://link-springer-com.ez88.periodicos.capes.gov.br/article/10.1007%2Fs00158-015-1366-1
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File SizeFormat 
000374972500008.pdf2.59 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.