Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Gaudrie, David"'
Publikováno v:
Structural and Multidisciplinary Optimization, 2020, 61, pp.2343-2361
Parametric shape optimization aims at minimizing an objective function f(x) where x are CAD parameters. This task is difficult when f is the output of an expensive-to-evaluate numerical simulator and the number of CAD parameters is large. Most often,
Externí odkaz:
http://arxiv.org/abs/1908.11272
Publikováno v:
Annals of Mathematics and Artificial Intelligence volume 88, pages 187-212(2020)
Multi-objective optimization aims at finding trade-off solutions to conflicting objectives. These constitute the Pareto optimal set. In the context of expensive-to-evaluate functions, it is impossible and often non-informative to look for the entire
Externí odkaz:
http://arxiv.org/abs/1811.03862
Optimizing nonlinear systems involving expensive computer experiments with regard to conflicting objectives is a common challenge. When the number of experiments is severely restricted and/or when the number of objectives increases, uncovering the wh
Externí odkaz:
http://arxiv.org/abs/1809.10482
Publikováno v:
Computational Statistics; Sep2024, Vol. 39 Issue 6, p3049-3071, 23p
Akademický článek
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Publikováno v:
Journées Scientifiques du CIROQUO
Journées Scientifiques du CIROQUO, Consortium en mathématiques appliquées CIROQUO, May 2023, Palaiseau, France
Journées Scientifiques du CIROQUO, Consortium en mathématiques appliquées CIROQUO, May 2023, Palaiseau, France
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2885::0f51cc1c4af2950c4792fa6d812e8f8d
https://hal.science/hal-04115494/document
https://hal.science/hal-04115494/document
Publikováno v:
MASCOT-NUM2023
MASCOT-NUM2023, Apr 2023, LE CROISIC, France
MASCOT-NUM2023, Apr 2023, LE CROISIC, France
International audience; Numerical optimization has been widely used to solve design engineering problems in recent years. However, due to the large number of numerical simulations required, the optimization process involved is often computationally e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2885::0a21066a76924997134e7e94f8ce2788
https://hal.science/hal-04102201
https://hal.science/hal-04102201
Kriging metamodeling (also called Gaussian Process regression) is a popular approach to predict the output of a function based on few observations. The Kriging method involves length-scale hyperparameters whose optimization is essential to obtain an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::86207239a008dc56983c09491a092a85
https://hal.science/hal-03812073
https://hal.science/hal-03812073
Autor:
Le Riche, Rodolphe, Gaudrie, David, Cuesta-Ramirez, Jhouben, Salah, Sami Ben Elhaj, Roustant, Olivier, Picheny, Victor, Durrande, Nicolas, Bay, Xavier, Bruchon, Julien, Moulin, Nicolas
Publikováno v:
Journée scientifique de la SF2M: matériau numérique
Journée scientifique de la SF2M: matériau numérique, SF2M, Mar 2022, Paris, France
Journée scientifique de la SF2M: matériau numérique, SF2M, Mar 2022, Paris, France
National audience; Data-driven approaches to modeling and design in mechanics often assume, when relying on neural networks, that a large amount of data is available. However, this is not always the case as the experiments or the physical simulations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::629e4c4ae8fa966a8ba79ad9d6289212
https://hal.archives-ouvertes.fr/hal-03605952
https://hal.archives-ouvertes.fr/hal-03605952
Publikováno v:
PGMO Days 2019
PGMO Days 2019, Dec 2019, Saclay, France
PGMO Days 2019, Dec 2019, Saclay, France
International audience; Parametric shape optimization aims at minimizing a function f(x) where x ∈ X ⊂ Rd is a vector of d Computer Aided Design parameters, representing diverse characteristics of the shap e Ω x . It is common for d to be large
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::940afca06b1103805582d8ed9483f9e0
https://hal-emse.ccsd.cnrs.fr/emse-02440143
https://hal-emse.ccsd.cnrs.fr/emse-02440143