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Conference Paper: HTS coil design using artificial neural network and fuzzy interference system

TitleHTS coil design using artificial neural network and fuzzy interference system
Authors
Issue Date2003
PublisherInternational Society for Magnetic Resonance in Medicine (ISMRM)
Citation
International Society for Magnetic Resonance in Medicine (ISMRM) 11th Scientific Meeting & Exhibition, Toronto, Canada, 10-16 July 2003, p. 2380 How to Cite?
AbstractThe design of High Temperature Superconducting (HTS) RF coil highly relies on the computer simulation because HTS materials are very expensive and the coil fabrication requires high accuracy. Normally, the simulation for the HTS coil design is time consuming and not straightforward. In this paper, two novel approaches for HTS coil design, the electromagnetically (EM) trained artificial neural networks (EM-ANN) and the electromagnetically trained fuzzy inference systems (EM-FIS) are presented. These two models can simplify the normal simulation and speed up by millions of times. Therefore, the difficult tuning procedure of HTS coil can be easily simulated before its fabrication.
Persistent Identifierhttp://hdl.handle.net/10722/99489
ISSN

 

DC FieldValueLanguage
dc.contributor.authorHui, Pen_HK
dc.contributor.authorShen, GGen_HK
dc.date.accessioned2010-09-25T18:32:29Z-
dc.date.available2010-09-25T18:32:29Z-
dc.date.issued2003en_HK
dc.identifier.citationInternational Society for Magnetic Resonance in Medicine (ISMRM) 11th Scientific Meeting & Exhibition, Toronto, Canada, 10-16 July 2003, p. 2380en_HK
dc.identifier.issn1545-4428-
dc.identifier.urihttp://hdl.handle.net/10722/99489-
dc.description.abstractThe design of High Temperature Superconducting (HTS) RF coil highly relies on the computer simulation because HTS materials are very expensive and the coil fabrication requires high accuracy. Normally, the simulation for the HTS coil design is time consuming and not straightforward. In this paper, two novel approaches for HTS coil design, the electromagnetically (EM) trained artificial neural networks (EM-ANN) and the electromagnetically trained fuzzy inference systems (EM-FIS) are presented. These two models can simplify the normal simulation and speed up by millions of times. Therefore, the difficult tuning procedure of HTS coil can be easily simulated before its fabrication.-
dc.languageengen_HK
dc.publisherInternational Society for Magnetic Resonance in Medicine (ISMRM)-
dc.relation.ispartofInternational Society for Magnetic Resonance in Medicine (ISMRM) Scientific Meeting & Exhibitionen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleHTS coil design using artificial neural network and fuzzy interference systemen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailShen, GG: gxshen@eee.hku.hken_HK
dc.identifier.authorityShen, GG=rp00166en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.hkuros83013en_HK
dc.identifier.spage2380en_HK

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