EFFICIENT BAYESIAN MULTIFIDELITY APPROACH IN METAMODELING OF AN ELECTROMAGNETIC SIMULATOR RESPONSE
Author(s) -
Tarek Bdour,
Christopher Guiffaut,
Alain Reineix
Publication year - 2017
Publication title -
progress in electromagnetics research m
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 31
ISSN - 1937-8726
DOI - 10.2528/pierm16120103
Subject(s) - metamodeling , computer science , bayesian probability , simulation , artificial intelligence , software engineering
Several computer codes with varying accuracy from rigorous full-wave methods (highfidelity models) to less accurate Transmission Line (TL) approaches (low-fidelity model) have been proposed to solve EMC problems of interference between parasitic waves and wired communication systems. For solving engineering tasks, with a limited computational budget, we need to build surrogate models of high-fidelity (HF) computer codes. However, one of their main limitations is their expensive computational time. Rather than using only the computationally costly HF simulations, we apply another type of surrogate models, called Multifidelity (MF) metamodel which efficiently combines, within a Bayesian framework, high and low-fidelity (LF) evaluations to speed up the surrogate model building. The numerical results of combination of an expensive EMC simulator and a cheap TL code to solve a plane wave illumination problem, show that, compared to Kriging, a reliable Bayesian MF metamodel of equivalent or higher predictivity can be obtained within less simulation time.
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