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Mathematical Problems in Engineering
Volume 2016, Article ID 6723410, 11 pages
http://dx.doi.org/10.1155/2016/6723410
Research Article

An Improved Approach for Estimating the Hyperparameters of the Kriging Model for High-Dimensional Problems through the Partial Least Squares Method

1Department of Aerospace Engineering, University of Michigan, 1320 Beal Avenue, Ann Arbor, MI 48109, USA
2ONERA, 2 Avenue Édouard Belin, 31055 Toulouse, France
3SNECMA, Rond-Point René Ravaud-Réau, 77550 Moissy-Cramayel, France
4Institut Clément Ader, CNRS, ISAE-SUPAERO, Université de Toulouse, 10 Avenue Edouard Belin, 31055 Toulouse Cedex 4, France

Received 31 December 2015; Revised 10 May 2016; Accepted 24 May 2016

Academic Editor: Erik Cuevas

Copyright © 2016 Mohamed Amine Bouhlel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [12 citations]

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  • Joan Mas Colomer, Nathalie Bartoli, Thierry Lefebvre, Sylvain Dubreuil, Joaquim Martins, Emmanuel Benard, and Joseph Morlier, “Similarity Maximization of a Scaled Aeroelastic Flight Demonstrator via Multidisciplinary Optimization,” 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, . View at Publisher · View at Google Scholar
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  • Thierry Lefebvre, Nathalie Bartoli, Sylvain Dubreuil, Marco Panzeri, Riccardo Lombardi, Wim Lammen, Mengmeng Zhang, Imco van Gent, and Pier Davide Ciampa, “A clustered and surrogate-based MDA use case for MDO scenarios in AGILE project,” 2018 Multidisciplinary Analysis and Optimization Conference, . View at Publisher · View at Google Scholar
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  • Mohamed Amine Bouhlel, Nathalie Bartoli, Rommel G. Regis, Abdelkader Otsmane, and Joseph Morlier, “Efficient global optimization for high-dimensional constrained problems by using the Kriging models combined with the partial least squares method,” Engineering Optimization, pp. 1–16, 2018. View at Publisher · View at Google Scholar
  • Mohamed Amine Bouhlel, John T. Hwang, Nathalie Bartoli, Rémi Lafage, Joseph Morlier, and Joaquim R.R.A. Martins, “A Python surrogate modeling framework with derivatives,” Advances in Engineering Software, pp. 102662, 2019. View at Publisher · View at Google Scholar
  • Glen T. Nwaila, Steven E. Zhang, Hartwig E. Frimmel, Musa S. D. Manzi, Christina Dohm, Raymond J. Durrheim, Mark Burnett, and Leon Tolmay, “Local and Target Exploration of Conglomerate-Hosted Gold Deposits Using Machine Learning Algorithms: A Case Study of the Witwatersrand Gold Ores, South Africa,” Natural Resources Research, 2019. View at Publisher · View at Google Scholar
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