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dc.contributor.authorYAŞAR, Esra
dc.contributor.authorUÇKUN, Ayşegül
dc.date.accessioned2019-07-10T08:02:18Z
dc.date.available2019-07-10T08:02:18Z
dc.date.issued2017-05
dc.identifier.urihttps://hdl.handle.net/20.500.12498/1009
dc.description.abstractEnergy demand isincreasing day by day in parallel with economic growth, especially for the rapidly developing countries. In order to achieve a sustainable economic growth, long-term targets are being put to manage the operation of market in a good way. Turkey isan emerging and rapidlydeveloping country soits energy demand has increased rapidly to meet the growing economy. Therefore, forecasting Turkey’s energy demand accurately is of great importance toachieve a sustainable economic growth. The main goal of this study is to develop the equation for forecasting energy demand using the backpropagationalgorithmwhich is one of the artificial neural-network models to determine the future level of energy demand.This study presents the predictions for the years 2017-2020.The results of the energy demand estimations found in this studyare compared with the official estimations of the MENR. It is concluded that official estimations for Turkey’s energy demand are dramatically higher than forecasting value presented in this study.en_US
dc.language.isoenen_US
dc.publisherInternational Renewable Energy Conference (IRENEC 2017)en_US
dc.subjectArtificial Neural-Network
dc.subjectTurkey
dc.subjectEnergy Demand Forecast
dc.titleTurkey’s Forecasting of Energy Demand with Artificial Neural-Networken_US
dc.typeKonferans Bildirisien_US


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