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Abstrakt
A surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through initial reduction of the design space. Optimization of the RSA model has been carried out using a multi-objective evolutionary algorithm (MOEA). Additional response correction techniques have been subsequently applied to improve selected designs at the high-fidelity EM antenna model level. The refined designs constitute the final Pareto set representation. The proposed approach has been validated using an ultra-wideband (UWB) monocone and a planar Yagi-Uda antenna.
Autorzy (3)
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Sławomir Kozieł prof. dr inż.
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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Leifur Leifsson
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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- Accepted albo Published Version
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- materiały konferencyjne indeksowane w Web of Science
- Opublikowano w:
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Procedia Computer Science
nr 29,
strony 790 - 799,
ISSN: 1877-0509 - Tytuł wydania:
- 2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE strony 790 - 799
- Język:
- angielski
- Rok wydania:
- 2014
- Opis bibliograficzny:
- Bekasiewicz A., Kozieł S., Leifsson L..: Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas, W: 2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, 2014, Elsevier,.
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 22 razy