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Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651435/ https://www.ncbi.nlm.nih.gov/pubmed/31324011 http://dx.doi.org/10.3390/s19133023 |
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author | Song, Yiran Cheng, Qingsha S. Koziel, Slawomir |
author_facet | Song, Yiran Cheng, Qingsha S. Koziel, Slawomir |
author_sort | Song, Yiran |
collection | PubMed |
description | In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation to construct a series of local surrogate models. In the optimization process, local region modeling and optimization are performed iteratively. A judgment factor is introduced to provide information for local region size update. The last local surrogate model is refined by space mapping techniques to obtain the optimal design with high accuracy. The operation and efficiency of the approach are demonstrated through design of a bandpass filter and a compact ultra-wide-band (UWB) multiple-in multiple-out (MIMO) antenna. The response of the optimized design of the fine model meet the design specification. The proposed method not only has better convergence compared to an existing local surrogate method, but also reduces the computational cost substantially. |
format | Online Article Text |
id | pubmed-6651435 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66514352019-08-08 Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization Song, Yiran Cheng, Qingsha S. Koziel, Slawomir Sensors (Basel) Article In order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation to construct a series of local surrogate models. In the optimization process, local region modeling and optimization are performed iteratively. A judgment factor is introduced to provide information for local region size update. The last local surrogate model is refined by space mapping techniques to obtain the optimal design with high accuracy. The operation and efficiency of the approach are demonstrated through design of a bandpass filter and a compact ultra-wide-band (UWB) multiple-in multiple-out (MIMO) antenna. The response of the optimized design of the fine model meet the design specification. The proposed method not only has better convergence compared to an existing local surrogate method, but also reduces the computational cost substantially. MDPI 2019-07-09 /pmc/articles/PMC6651435/ /pubmed/31324011 http://dx.doi.org/10.3390/s19133023 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Song, Yiran Cheng, Qingsha S. Koziel, Slawomir Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title | Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title_full | Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title_fullStr | Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title_full_unstemmed | Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title_short | Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization |
title_sort | multi-fidelity local surrogate model for computationally efficient microwave component design optimization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651435/ https://www.ncbi.nlm.nih.gov/pubmed/31324011 http://dx.doi.org/10.3390/s19133023 |
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