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https://hdl.handle.net/11499/4064
Title: | Application of Genetic Algorithm (GA) technique on demand estimation of fossil fuels in Turkey Conference Object] | Authors: | Canyurt, Olcay Ersel. Öztürk, Harun Kemal. |
Keywords: | Coal Energy sources Energy use Fossil fuel planning and projection Genetic algorithm Natural gas Oil Turkey Gross National Product (GNP) Genetic algorithms Fossil fuels |
Abstract: | The main objective of the present study is to investigate Turkey's fossil fuels demand, projection and supplies by giving the structure of the Turkish industry and Turkish economic conditions. This present study develops several scenarios to analyze fossil fuels; such as, coal, oil and natural gas consumption and make future projections based on Genetic Algorithm (GA) notion, and examines the effect of the design parameters on the fossil fuels utilization values. The models developed in the nonlinear form are applied to the coal, oil and natural gas demand of Turkey. Several Genetic Algorithm Demand Estimation Models (GA-DEM) are developed to estimate the future coal, oil and natural gas demand values based on population, Gross National Product (GNP), import, export figures. It may be concluded that the proposed models can be used as an alternative solution and estimation techniques for the future fossil fuel utilization values of any country. Oil is the most important fuel in Turkey, contributing 43% of the Total Primary Energy Supply (TPES), followed by coal (almost 30% of TPES) and natural gas (11.8%). In the study, coil, oil and natural gas consumption of Turkey are projected. Estimation shows that the coal, oil and natural gas consumption values may increase 2.82, 1.73 and 4.83 times from 2000 to 2020. Copyright © 2007 by ASME. | URI: | https://hdl.handle.net/11499/4064 https://doi.org/10.1115/ES2007-36260 |
ISBN: | 0791847977 9780791847978 |
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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