Electromagnetic device design based on RBF models and two new sequential optimization strategies

Lei, G; Yang, GY; Shao, KR; Guo, Y; Zhu, J; Lavers, JD

Electromagnetic device design based on RBF models and two new sequential optimization strategies

Lei, G

Yang, GY Shao, KR Guo, Y

Zhu, J

Lavers, JD

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Magnetics, 2010, 46 (8), pp. 3181 - 3184
Issue Date:: 2010-08-01

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Field	Value	Language
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802	en_US
dc.contributor.author	Yang, GY	en_US
dc.contributor.author	Shao, KR	en_US
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684	en_US
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047	en_US
dc.contributor.author	Lavers, JD	en_US
dc.date.issued	2010-08-01	en_US
dc.identifier.citation	IEEE Transactions on Magnetics, 2010, 46 (8), pp. 3181 - 3184	en_US
dc.identifier.issn	0018-9464	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15310
dc.description.abstract	We present two new strategies for sequential optimization method (SOM) to deal with the optimization design problems of electromagnetic devices. One is a new space reduction strategy; the other is model selection strategy. Meanwhile, radial basis function (RBF) and compactly supported RBF models are investigated to extend the applied model types for SOM. Thereafter, Monte Carlo method is employed to demonstrate the efficiency and superiority of the new space reduction strategy. Five commonly used approximate models are considered for the discussion of model selection strategy. Furthermore, by two TEAM benchmark examples, we can see that SOM with the proposed new strategies and models can significantly speed the optimization design process, and the efficiency of SOM depends a little on the types of approximate models. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Magnetics	en_US
dc.relation.isbasedon	10.1109/TMAG.2010.2043717	en_US
dc.subject.classification	Applied Physics	en_US
dc.title	Electromagnetic device design based on RBF models and two new sequential optimization strategies	en_US
dc.type	Journal Article
utslib.citation.volume	8	en_US
utslib.citation.volume	46	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	02 Physical Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
utslib.copyright.status	open_access
pubs.issue	8	en_US
pubs.publication-status	Published	en_US
pubs.volume	46	en_US

Abstract:

We present two new strategies for sequential optimization method (SOM) to deal with the optimization design problems of electromagnetic devices. One is a new space reduction strategy; the other is model selection strategy. Meanwhile, radial basis function (RBF) and compactly supported RBF models are investigated to extend the applied model types for SOM. Thereafter, Monte Carlo method is employed to demonstrate the efficiency and superiority of the new space reduction strategy. Five commonly used approximate models are considered for the discussion of model selection strategy. Furthermore, by two TEAM benchmark examples, we can see that SOM with the proposed new strategies and models can significantly speed the optimization design process, and the efficiency of SOM depends a little on the types of approximate models. © 2006 IEEE.

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