Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Brevault, Loïc"'
Multi-fidelity surrogate models combining dimensionality reduction and an intermediate surrogate in the reduced space allow a cost-effective emulation of simulators with functional outputs. The surrogate is an input-output mapping learned from a limi
Externí odkaz:
http://arxiv.org/abs/2408.17075
Autor:
Brevault, Loic, Balesdent, Mathieu
Complex system design problems, such as those involved in aerospace engineering, require the use of numerically costly simulation codes in order to predict the performance of the system to be designed. In this context, these codes are often embedded
Externí odkaz:
http://arxiv.org/abs/2310.05955
Autor:
Brevault, Loïc, Balesdent, Mathieu
Publikováno v:
In Engineering Applications of Artificial Intelligence July 2024 133 Part B
The design process of complex systems such as new configurations of aircraft or launch vehicles is usually decomposed in different phases which are characterized for instance by the depth of the analyses in terms of number of design variables and fid
Externí odkaz:
http://arxiv.org/abs/2006.16728
Multi-fidelity approaches combine different models built on a scarce but accurate data-set (high-fidelity data-set), and a large but approximate one (low-fidelity data-set) in order to improve the prediction accuracy. Gaussian Processes (GPs) are one
Externí odkaz:
http://arxiv.org/abs/2006.15924
Within the framework of complex system design, it is often necessary to solve mixed variable optimization problems, in which the objective and constraint functions can depend simultaneously on continuous and discrete variables. Additionally, complex
Externí odkaz:
http://arxiv.org/abs/2003.03300
Autor:
Balesdent, Mathieu, Brevault, Loïc, Paluch, Bernard, Thépot, Rémi, Wuilbercq, Romain, Subra, Naïr, Defoort, Sébastien, Bourgaie, Michel, Vieille, Bruno
Publikováno v:
In Acta Astronautica October 2023 211:97-115
Bayesian Optimization using Gaussian Processes is a popular approach to deal with the optimization of expensive black-box functions. However, because of the a priori on the stationarity of the covariance matrix of classic Gaussian Processes, this met
Externí odkaz:
http://arxiv.org/abs/1905.03350
Efficient Global Optimization (EGO) is widely used for the optimization of computationally expensive black-box functions. It uses a surrogate modeling technique based on Gaussian Processes (Kriging). However, due to the use of a stationary covariance
Externí odkaz:
http://arxiv.org/abs/1809.04632