Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4587
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dc.contributor.authorÖztürk, Harun Kemal-
dc.contributor.authorCanyurt, Olcay Ersel-
dc.contributor.authorHepbasli, A.-
dc.contributor.authorUtlu, Z.-
dc.date.accessioned2019-08-16T11:35:14Z
dc.date.available2019-08-16T11:35:14Z
dc.date.issued2006-
dc.identifier.issn1556-7036-
dc.identifier.urihttps://hdl.handle.net/11499/4587-
dc.identifier.urihttps://doi.org/10.1080/009083190881490-
dc.description.abstractSince 1975, there has been a great deal of interest, particularly during the past decade, in the promising genetic algorithm (GA) and its application to various disciplines from medicine to cogeneration. However, the studies performed on energy-related GA modeling are relatively low in numbers. The main objective of the present study is to develop the exergy input/output estimation equations in order to estimate the future projections based on the GA notion. In this regard, the GA Future Total EXergy Input/Output Estimation Models (GAFTEXIEM/GAFTEXOEM) are used to estimate total exergy input/output demand of Turkey, which is selected as an application country, based on the economic and social indicators of gross domestic product (GDP), population, import, export and house production figures. The future prediction of Turkey's total exergy input/output values are projected between 2003 and 2023. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies.en_US
dc.language.isoenen_US
dc.relation.ispartofEnergy Sources, Part A: Recovery, Utilization and Environmental Effectsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEnergy modelingen_US
dc.subjectEnergy planningen_US
dc.subjectEnergy useen_US
dc.subjectExergyen_US
dc.subjectFuture projectionsen_US
dc.subjectGenetic algorithmen_US
dc.subjectCogeneration plantsen_US
dc.subjectEconomic and social effectsen_US
dc.subjectEnergy managementen_US
dc.subjectEnergy policyen_US
dc.subjectEstimationen_US
dc.subjectMathematical modelsen_US
dc.subjectMedicineen_US
dc.subjectEnergyen_US
dc.subjectGenetic algorithmsen_US
dc.titleAn application of genetic algorithm search techniques to the future total exergy input/output estimationen_US
dc.typeReviewen_US
dc.identifier.volume28en_US
dc.identifier.issue8en_US
dc.identifier.startpage715
dc.identifier.startpage715en_US
dc.identifier.endpage725en_US
dc.authorid0000-0003-4831-1118-
dc.authorid0000-0003-3690-6608-
dc.identifier.doi10.1080/009083190881490-
dc.relation.publicationcategoryDiğeren_US
dc.identifier.scopus2-s2.0-33646776446en_US
dc.identifier.wosWOS:000237274300003en_US
dc.identifier.scopusquality--
dc.ownerPamukkale_University-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeReview-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept10.07. Mechanical Engineering-
crisitem.author.dept10.07. Mechanical Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Tıp Fakültesi Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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