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The consideration of surrogate model accuracy in single-objective electromagnetic design optimization

The consideration of surrogate model accuracy in single-objective electromagnetic design optimization
The consideration of surrogate model accuracy in single-objective electromagnetic design optimization
The computational cost of evaluating the objective function in electromagnetic optimal design problems necessitates the use of cost-effective techniques. This paper describes how one popular technique, surrogate modelling, has been used in the single-objective optimization of electromagnetic devices. Three different types of surrogate model are considered, namely polynomial approximation, artificial neural networks and kriging. The importance of considering surrogate model accuracy is emphasised, and techniques used to improve accuracy for each type of model are discussed. Developments in this area outside the field of electromagnetic design optimization are also mentioned. It is concluded that surrogate model accuracy is an important factor which should be considered during an optimization search, and that developments have been made elsewhere in this area which are yet to be implemented in electromagnetic design optimization.
978-3-8007-2957-9
115-116
Hawe, G.I.
649d9e56-696a-4aef-a882-832d5f94a094
Sykulski, J.K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Hawe, G.I.
649d9e56-696a-4aef-a882-832d5f94a094
Sykulski, J.K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Hawe, G.I. and Sykulski, J.K. (2006) The consideration of surrogate model accuracy in single-objective electromagnetic design optimization. In Proceedings of Sixth International Conference on Computational Electromagnetics. pp. 115-116 .

Record type: Conference or Workshop Item (Paper)

Abstract

The computational cost of evaluating the objective function in electromagnetic optimal design problems necessitates the use of cost-effective techniques. This paper describes how one popular technique, surrogate modelling, has been used in the single-objective optimization of electromagnetic devices. Three different types of surrogate model are considered, namely polynomial approximation, artificial neural networks and kriging. The importance of considering surrogate model accuracy is emphasised, and techniques used to improve accuracy for each type of model are discussed. Developments in this area outside the field of electromagnetic design optimization are also mentioned. It is concluded that surrogate model accuracy is an important factor which should be considered during an optimization search, and that developments have been made elsewhere in this area which are yet to be implemented in electromagnetic design optimization.

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More information

Published date: 2006
Additional Information: CEM 2006, 4 - 6 April 2006, Aachen, Germany
Organisations: EEE

Identifiers

Local EPrints ID: 262280
URI: http://eprints.soton.ac.uk/id/eprint/262280
ISBN: 978-3-8007-2957-9
PURE UUID: 740e050a-68bd-4ba5-a55f-13d443b471cc
ORCID for J.K. Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

Catalogue record

Date deposited: 07 Apr 2006
Last modified: 15 Mar 2024 02:34

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Contributors

Author: G.I. Hawe
Author: J.K. Sykulski ORCID iD

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