Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey

Autor: Hanane Khatouri, Tariq Benamara, Piotr Breitkopf, Jean Demange

Publikováno v: Advanced Modeling and Simulation in Engineering Sciences, Vol 9, Iss 1, Pp 1-31 (2022)

Abstract In design optimization of complex systems, the surrogate model approach relying on progressively enriched Design of Experiments (DOE) avoids efficiency problems encountered when embedding simulation codes within optimization loops. However,

Externí odkaz: https://doaj.org/article/4aedb04ddefb450db13a22848442cae3

Multi-Fidelity Aerodynamic Data Fusion with a Deep Neural Network Modeling Method

Autor: Lei He, Weiqi Qian, Tun Zhao, Qing Wang

Publikováno v: Entropy, Vol 22, Iss 9, p 1022 (2020)

To generate more high-quality aerodynamic data using the information provided by different fidelity data, where low-fidelity aerodynamic data provides the trend information and high-fidelity aerodynamic data provides value information, we applied a d

Externí odkaz: https://doaj.org/article/eb67891ece184114b22d99930922a072

Comparing Two Multivariable Complexity Functions Using One-variable Complexity Classes

Autor: Andrei Horia MOGOS, Adina Magda FLOREA

Publikováno v: Informatică economică, Vol 13, Iss 4, Pp 116-128 (2009)

The comparison of algorithms complexities is very important both in theory and in practice. When we compare algorithms complexities we need to compare complexity functions. Usually we use one-variable complexity functions. Sometimes, we need multivar

Externí odkaz: https://doaj.org/article/c2b4f88ac5b04c279f4284f7a055ac9f

Constrained multi-fidelity surrogate framework using Bayesian optimization with non-intrusive reduced-order basis

Autor: Paul Feliot, Piotr Breitkopf, Hanane Khatouri, Jean Demange, Tariq Benamara

Publikováno v: Advanced Modeling and Simulation in Engineering Sciences
Advanced Modeling and Simulation in Engineering Sciences, SpringerOpen, 2020, 7 (1), ⟨10.1186/s40323-020-00176-z⟩
Advanced Modeling and Simulation in Engineering Sciences, Vol 7, Iss 1, Pp 1-20 (2020)

This article addresses the problem of constrained derivative-free optimization in a multi-fidelity (or variable-complexity) framework using Bayesian optimization techniques. It is assumed that the objective and constraints involved in the optimizatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f86347e28d3400371c9878ba54b49c6d
https://doi.org/10.1186/s40323-020-00176-z

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