An improved approach for estimating the hyperparameters of the Kriging model for high-dimensional problems through the partial least squares method
type: Item
instance of: scholarly article
title: An improved approach for estimating the hyperparameters of the Kriging model for high-dimensional problems through the partial least squares method
zbMATH Open document ID: 1400.62110
DOI: 10.1155/2016/6723410
author: Mohamed Amine Bouhlel
author: Nathalie Bartoli
author: Abdelkader Otsmane
author: Joseph Morlier
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: During the last years, kriging has become one of the most popular methods in computer simulation and machine learning. Kriging models have been successfully used in many engineering applications, to approximate expensive simulation models. When many input variables are used, kriging is inefficient mainly due to an exorbitant computational time required during its construction. To handle high-dimensional problems (100+), one method is recently proposed that combines kriging with the Partial Least Squares technique, the so-called KPLS model. This method has shown interesting results in terms of saving CPU time required to build model while maintaining sufficient accuracy, on both academic and industrial problems. However, KPLS has provided a poor accuracy compared to conventional kriging on multimodal functions. To handle this issue, this paper proposes adding a new step during the construction of KPLS to improve its accuracy for multimodal functions. When the exponential covariance functions are used, this step is based on simple identification between the covariance function of KPLS and kriging. The developed method is validated especially by using a multimodal academic function, known as Griewank function in the literature, and we show the gain in terms of accuracy and computer time by comparing with KPLS and kriging.
Mathematics Subject Classification ID: 62H11
zbMATH DE Number: 6953466
describes a project that uses: EGO
describes a project that uses: DiceOptim
describes a project that uses: DiceKriging
describes a project that uses: Scikit
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/6723410
OpenAlex ID: W2468770775
Wikidata QID: Q59141095
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description: scientific article; zbMATH DE number 6953466