On-line combined use of neural networks and genetic algorithms to the solution of transformer iron loss reduction problem

Georgilakis, P; Hatziargyriou, N; Paparigas, D; Bakopoulos, J

dc.contributor.author	Georgilakis, P	en
dc.contributor.author	Hatziargyriou, N	en
dc.contributor.author	Paparigas, D	en
dc.contributor.author	Bakopoulos, J	en
dc.date.accessioned	2014-03-01T01:48:13Z
dc.date.available	2014-03-01T01:48:13Z
dc.date.issued	1999	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25431
dc.subject	Genetic Algorithm	en
dc.subject	Group Process	en
dc.subject	Iron	en
dc.subject	Neural Network	en
dc.title	On-line combined use of neural networks and genetic algorithms to the solution of transformer iron loss reduction problem	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/PTC.1999.826586	en
heal.identifier.secondary	http://dx.doi.org/10.1109/PTC.1999.826586	en
heal.publicationDate	1999	en
heal.abstract	A new approach using neural networks and genetic algorithms to solve the transformer iron loss reduction problem is proposed in this paper. Neural networks are used to predict iron losses of wound core distribution transformers at the early stages of transformer construction. Moreover, genetic algorithms are combined with neural networks in order to improve the grouping process of the individual	en
dc.identifier.doi	10.1109/PTC.1999.826586	en