Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4478
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dc.contributor.authorCanyurt, Olcay Ersel.-
dc.contributor.authorÖztürk, Harun Kemal.-
dc.date.accessioned2019-08-16T11:34:20Z
dc.date.available2019-08-16T11:34:20Z
dc.date.issued2006-
dc.identifier.issn0196-8904-
dc.identifier.urihttps://hdl.handle.net/11499/4478-
dc.identifier.urihttps://doi.org/10.1016/j.enconman.2006.03.009-
dc.description.abstractThis present study develops three scenarios to analyze oil consumption and make future projections based on the Genetic algorithm (GA) notion, and examines the effect of the design parameters on the oil utilization values. The models developed in the non-linear form are applied to the oil demand of Turkey. The GA Oil Demand Estimation Model (GAODEM) is developed to estimate the future oil demand values based on Gross National Product (GNP), population, import, export, oil production, oil import and car, truck and bus sales figures. Among these models, the GA-PGOiTI model, which uses population, GNP, oil import, truck sales and import as design parameters/indicators, was found to provide the best fit solution with the observed data. It may be concluded that the proposed models can be used as alternative solution and estimation techniques for the future oil utilization values of any country. © 2006 Elsevier Ltd. All rights reserved.en_US
dc.language.isoenen_US
dc.relation.ispartofEnergy Conversion and Managementen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFuture projectionsen_US
dc.subjectGenetic algorithmen_US
dc.subjectOil consumptionen_US
dc.subjectOil demanden_US
dc.subjectOil planningen_US
dc.subjectOil policyen_US
dc.subjectTurkeyen_US
dc.subjectEstimationen_US
dc.subjectFuel consumptionen_US
dc.subjectGround vehiclesen_US
dc.subjectInternational tradeen_US
dc.subjectMathematical modelsen_US
dc.subjectPopulation statisticsen_US
dc.subjectProblem solvingen_US
dc.subjectProduction controlen_US
dc.subjectGenetic algorithmsen_US
dc.titleThree different applications of genetic algorithm (GA) search techniques on oil demand estimationen_US
dc.typeArticleen_US
dc.identifier.volume47en_US
dc.identifier.issue18-19en_US
dc.identifier.startpage3138
dc.identifier.startpage3138en_US
dc.identifier.endpage3148en_US
dc.authorid0000-0003-3690-6608-
dc.authorid0000-0003-4831-1118-
dc.identifier.doi10.1016/j.enconman.2006.03.009-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-33745922353en_US
dc.identifier.wosWOS:000239823900025en_US
local.message.claim2023-07-12T13:21:16.695+0300|||rp00390|||submit_approve|||dc_contributor_author|||None*
dc.identifier.scopusqualityQ1-
dc.ownerPamukkale_University-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeArticle-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
crisitem.author.dept10.07. Mechanical Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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