Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/4587
Title: | An application of genetic algorithm search techniques to the future total exergy input/output estimation | Authors: | Öztürk, Harun Kemal Canyurt, Olcay Ersel Hepbasli, A. Utlu, Z. |
Keywords: | Energy modeling Energy planning Energy use Exergy Future projections Genetic algorithm Cogeneration plants Economic and social effects Energy management Energy policy Estimation Mathematical models Medicine Energy Genetic algorithms |
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. | URI: | https://hdl.handle.net/11499/4587 https://doi.org/10.1080/009083190881490 |
ISSN: | 1556-7036 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection Tıp Fakültesi Koleksiyonu WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Show full item record
CORE Recommender
SCOPUSTM
Citations
7
checked on Nov 16, 2024
WEB OF SCIENCETM
Citations
6
checked on Nov 15, 2024
Page view(s)
32
checked on Aug 24, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.