A new algorithm based on artificial bee colony algorithm for energy demand forecasting in Turkey

Basit Öğe Kaydı
dc.contributor.authorUguz, Harun
dc.contributor.authorHakli, Huseyin
dc.contributor.authorBaykan, Omer K.
dc.date.accessioned2020-03-26T19:00:26Z
dc.date.available2020-03-26T19:00:26Z
dc.date.issued2015
dc.departmentSelçuk Üniversitesien_US
dc.description4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT) -- DEC 08-10, 2015 -- Kuala Lumpur, MALAYSIAen_US
dc.description.abstractIn this study, an energy demand forecasting algorithm based on the Artificial Bee Colony with Variable Search Strategies (ABCVSS) method was proposed in order to determine Turkey's long-term energy demand. Linear and quadratic equations were used for energy demand forecasting and the coefficients of the equations were determined by means of the ABCVSS method. With the ABCVSS method, an attempt was made to enhance the local and global searching capacity of the ABC algorithm by using five different search strategies. GDP, population, imports and exports data of the period from 1979 to 2005 were chosen as the input parameters for the proposed method. Long-term energy demand was predicted through one scenario and the obtained performance from the proposed method was compared to those obtained from PSO, ACO and HAP algorithms in the literature. It was determined that the proposed method is statistically more successful than the other methods.en_US
dc.description.sponsorshipDesign sci Renaissance, UNiTECH, PECAMP, MSTIen_US
dc.description.sponsorshipScientific and Technological Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)en_US
dc.description.sponsorshipThis study has been supported by The Scientific and Technological Research Council of Turkey.en_US
dc.identifier.doi10.1109/ACSAT.2015.12en_US
dc.identifier.endpage61en_US
dc.identifier.isbn978-1-5090-0424-9
dc.identifier.issn2379-7738en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage56en_US
dc.identifier.urihttps://dx.doi.org/10.1109/ACSAT.2015.12
dc.identifier.urihttps://hdl.handle.net/20.500.12395/31768
dc.identifier.wosWOS:000454655600011en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2015 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT)en_US
dc.relation.ispartofseriesInternational Conference on Advanced Computer Science Applications and Technologies
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial bee colonyen_US
dc.subjectEnergy demanden_US
dc.subjectEstimationen_US
dc.subjectOptimizationen_US
dc.subjectTurkeyen_US
dc.titleA new algorithm based on artificial bee colony algorithm for energy demand forecasting in Turkeyen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu