No-load loss modelling of wound-core transformers using support vector machines and genetic algorithms

Passadis, K; Loizos, G; Kladas, A

dc.contributor.author	Passadis, K	en
dc.contributor.author	Loizos, G	en
dc.contributor.author	Kladas, A	en
dc.date.accessioned	2014-03-01T02:53:22Z
dc.date.available	2014-03-01T02:53:22Z
dc.date.issued	2011	en
dc.identifier.issn	02555476	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36275
dc.subject	Distribution transformers	en
dc.subject	Estimation techniques	en
dc.subject	Model	en
dc.subject	Support vector machines	en
dc.subject.other	Accurate estimation	en
dc.subject.other	Core material	en
dc.subject.other	Distribution transformer	en
dc.subject.other	Estimation techniques	en
dc.subject.other	No-load loss	en
dc.subject.other	Transformer design	en
dc.subject.other	Coremaking	en
dc.subject.other	Electric load loss	en
dc.subject.other	Electromagnetism	en
dc.subject.other	Estimation	en
dc.subject.other	Magnetic materials	en
dc.subject.other	Superconducting materials	en
dc.subject.other	Superconductivity	en
dc.subject.other	Vectors	en
dc.subject.other	Support vector machines	en
dc.title	No-load loss modelling of wound-core transformers using support vector machines and genetic algorithms	en
heal.type	conferenceItem	en
heal.identifier.primary	10.4028/www.scientific.net/MSF.670.425	en
heal.identifier.secondary	http://dx.doi.org/10.4028/www.scientific.net/MSF.670.425	en
heal.publicationDate	2011	en
heal.abstract	Accurate estimation of no-load losses is crucial in the transformer design procedure. It saves engineering man-hours, reduces delivery cycle and optimizes the use of core materials. The aim of this paper is to show that Support Vector Machines (SVM) can be successfully used to estimate no load losses.	en
heal.journalName	Materials Science Forum	en
dc.identifier.doi	10.4028/www.scientific.net/MSF.670.425	en
dc.identifier.volume	670	en
dc.identifier.spage	425	en
dc.identifier.epage	431	en