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The local power demand estimation based on artificial neural network technique

dc.contributor.authorKilic, O
dc.contributor.authorAttar, F
dc.contributor.authorYumurtaci, R
dc.contributor.authorTanrioven, M
dc.date.accessioned2026-06-27T12:56:22Z
dc.date.issued1998
dc.description.abstractThe demand to electrical energy increases day by day. It is very important to reflect this increasing demand accurately to power plant planning. ANN technique can be effectively used in loan forecasting. In this paper, ANN load forecasting is performed by using some non-linear input parameters such as temperature, humidity, rain conditions. Real electrical date obtained for the national grid and meteorological parameters are used in the presented application.en
dc.identifier.endpage991
dc.identifier.isbn0-7803-3879-0
dc.identifier.issn0843-932X
dc.identifier.startpage988
dc.identifier.urihttps://hdl.handle.net/20.500.14981/47904
dc.identifier.wos000075341900213
dc.language.isoeng
dc.publisherIEEE
dc.relation.conference9th Mediterranean Electrotechnical Conference (Melecon 98)
dc.relation.ispartofMELECON '98 - 9TH MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, VOLS 1 AND 2
dc.subjectartificial neural network
dc.subjectbackpropagation algorithms
dc.subjectlearning rate
dc.subjectload forecasting
dc.subjectneuron
dc.subjectAutomation & Control Systems
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectOptics
dc.subjectTelecommunications
dc.titleThe local power demand estimation based on artificial neural network technique
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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