Overview and Comparison of Gaussian Process-Based Surrogate Models for Mixed Continuous and Discrete Variables: Application on Aerospace Design Problems
| Autor: | Yannick Guerin, El-Ghazali Talbi, Mathieu Balesdent, Julien Pelamatti, Loïc Brevault |
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| Přispěvatelé: | DTIS, ONERA, Université Paris Saclay (COmUE) [Palaiseau], ONERA-Université Paris Saclay (COmUE), Optimisation de grande taille et calcul large échelle (BONUS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Centre de Recherche Réseau Image SysTème Architecture et MuLtimédia (CRISTAL), École Nationale des Sciences de l'Informatique [Manouba] (ENSI), Université de la Manouba [Tunisie] (UMA)-Université de la Manouba [Tunisie] (UMA), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
021103 operations research business.industry Discrete functions Computer science 0211 other engineering and technologies Complex system 02 engineering and technology 01 natural sciences [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] 010104 statistics & probability symbols.namesake [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] symbols [INFO]Computer Science [cs] 0101 mathematics Engineering design process Aerospace business Gaussian process |
| Zdroj: | High-Performance Simulation-Based Optimization High-Performance Simulation-Based Optimization, Springer, pp.189-224, 2020, ⟨10.1007/978-3-030-18764-4_9⟩ High-Performance Simulation-Based Optimization ISBN: 9783030187637 |
| Popis: | International audience; Surrogate modeling is an increasingly popular tool for engineering design as it enables to model the performance of very complex systems with a limited computational cost. A large number of techniques exists for the surrogate modeling of continuous functions, however, only a very few methods for the surrogate modeling of mixed continuous/discrete functions have been developed. In this chapter, existing adaptations and variants of Gaussian process-based surrogate modeling techniques for mixed continuous/discrete variables are described, discussed and compared on several analytical test-cases and aerospace design problems. |
| Databáze: | OpenAIRE |
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