Forecasting of Turkey’s Electricity Consumption with Support Vector Regression and Chaotic Particle Swarm Algorithm

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dc.authoridTR101147en_US
dc.authoridTR103344en_US
dc.authoridTR101378en_US
dc.contributor.authorKaynar, Oğuz
dc.contributor.authorÖzekicioğlu, Halil
dc.contributor.authorDemirkoparan, Ferhan
dc.date.accessioned2017-05-18T11:35:14Z
dc.date.available2017-05-18T11:35:14Z
dc.date.issued2017-02
dc.description.abstractEnergy is a very important factor in terms of sustaining the economic development for developing and industrialized countries. Electricity is one of the most important forms of energy for industrialization and improvement of living standards. The estimation and modeling of electricity consumption has a special importance in Turkey which is a foreign-dependent country in energy. In this study, a forecasting application is made by using Turkey’s electricity consumption, population, import, export and gross domestic product between 1975-2014 employing support vector regression methods. Chaotic particle swarm optimization algorithm (CPSO) is used to choose the parameters of SVR.en_US
dc.identifier.citationKaynar, O., Özekicioğlu, H. ve Demirkoparan, F. (2017).Forecasting of Turkey’s Electricity Consumption with Support Vector Regression and Chaotic Particle Swarm Algorithm. Yönetim Bilimleri Dergisi, 15, 211-224.en_US
dc.identifier.issn1304-5318
dc.identifier.urihttps://hdl.handle.net/20.500.12428/1706
dc.institutionauthor. . .en_US
dc.language.isoen
dc.publisherÇanakkale Onsekiz Mart Üniversitesien_US
dc.relation.ispartofYönetim Bilimleri Dergisien_US
dc.relation.publicationcategory. . .en_US
dc.rights.uriinfo:eu-repo/semantics/openAccessen_US
dc.subjectElectricity consumptionen_US
dc.subjectSupport Vector Regressionen_US
dc.subjectChaotic Particle Swarm Optimization Algorithmen_US
dc.subjectPredictionen_US
dc.titleForecasting of Turkey’s Electricity Consumption with Support Vector Regression and Chaotic Particle Swarm Algorithm
dc.typeArticle

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