Short term load forecasting using fuzzy neural networks

Bakirtzis, A; Theocharis, J; Kiartzis, S; Satsios, K

dc.contributor.author	Bakirtzis, A	en
dc.contributor.author	Theocharis, J	en
dc.contributor.author	Kiartzis, S	en
dc.contributor.author	Satsios, K	en
dc.date.accessioned	2014-03-01T01:43:28Z
dc.date.available	2014-03-01T01:43:28Z
dc.date.issued	1995	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24126
dc.subject	Fuzzy Neural Network	en
dc.subject	Fuzzy System	en
dc.subject	Network Structure	en
dc.subject	Short Term Load Forecasting	en
dc.subject	Neural Network	en
dc.subject	Rule Based	en
dc.title	Short term load forecasting using fuzzy neural networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/59.466494	en
heal.identifier.secondary	http://dx.doi.org/10.1109/59.466494	en
heal.publicationDate	1995	en
heal.abstract	This paper presents the development of a fuzzy system for short term load forecasting. The fuzzy system has the network structure and the training procedure of a neural network and is called a fuzzy neural network (FNN). An FNN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a	en
heal.journalName	IEEE Transactions on Power Systems	en
dc.identifier.doi	10.1109/59.466494	en