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An application of genetic algorithm search techniques to the future total exergy input/output estimation

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dc.contributor.author Ozturk, H.K.
dc.contributor.author Canyurt, O.E.
dc.contributor.author Hepbasli, A.
dc.contributor.author Utlu, Z.
dc.date.accessioned 2019-08-16T11:35:14Z
dc.date.available 2019-08-16T11:35:14Z
dc.date.issued 2006
dc.identifier.issn 15567036 (ISSN)
dc.identifier.uri http://acikerisim.pau.edu.tr:8080/xmlui/handle/11499/4587
dc.description.abstract Since 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.
dc.language.iso English
dc.relation.isversionof 10.1080/009083190881490
dc.subject Energy modeling
dc.subject Energy planning
dc.subject Energy use
dc.subject Exergy
dc.subject Future projections
dc.subject Genetic algorithm
dc.subject Cogeneration plants
dc.subject Economic and social effects
dc.subject Energy management
dc.subject Energy policy
dc.subject Estimation
dc.subject Mathematical models
dc.subject Medicine
dc.subject Energy
dc.subject Genetic algorithms
dc.title An application of genetic algorithm search techniques to the future total exergy input/output estimation
dc.type Review
dc.relation.journal Energy Sources, Part A: Recovery, Utilization and Environmental Effects
dc.identifier.volume 28
dc.identifier.issue 8
dc.identifier.startpage 715
dc.identifier.endpage 725
dc.identifier.index Scopus


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