General Information
    • ISSN: 1793-821X
    • Frequency: Quarterly (2013-2014); Bimonthly (Since 2015)
    • DOI: 10.18178/JOCET
    • Editor-in-Chief: Prof. Haider F. Abdul Amir
    • Executive Editor: Ms. Jennifer Zeng
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library, Chemical Abstracts Services (CAS), Ulrich's Periodicals Directory, Google Scholar, ProQuest.
    • E-mail: jocet@ejournal.net
  • Nov 15, 2018 News! JOCET Vol. 6, No. 6 is available online now.   [Click]
  • Sep 20, 2018 News! JOCET Vol. 6, No. 5 is available online now. 7 papers which cover 2 specific areas are published in this issue.   [Click]
Editor-in-chief
School of Science and Technology Universiti Malaysia Sabah, Malaysia.
I would like to express my appreciation to all authors, reviewers and edtors.
JOCET 2018 Vol.6(4): 349-352 ISSN: 1793-821X
DOI: 10.18178/JOCET.2018.6.4.486

Comparing Energy Demand Estimation Using Artificial Algae Algorithm: The Case of Turkey

Ayşe Beşkirli, Mehmet Beşkirli, Hüseyin Haklı, and Harun Uğuz
Abstract—Energy demand estimation is an important issue in terms of the economy and resources of a country. In this study, an Artificial Algae Algorithm (AAA) was used to estimate Turkey’s long-term energy demand. The AAA is a fast, powerful and effective evolutionary optimization technique used to solve continuous optimization problems. Two different equations (linear and exponential) were used for the energy demand estimation by considering the relationship between the increase in economic indicators and the increase in energy consumption in Turkey. Turkey’s long-term energy demand was estimated from 2006 to 2025 with the AAA method by using gross national product (GNP) and information about imports, exports and population. The AAA method was compared to other methods in published literature to show its success when applied to the energy demand problem. It was found that the results obtained by the proposed method were more robust and successful than those of the other methods.

Index Terms—Artificial algae algorithm, optimization, energy demand, estimation, Turkey.

A. Beşkirli is with the Computer Engineering Department, Dumlupınar University, Kütahya, Turkey (e-mail: ayse.beskirli@ogr.dpu.edu.tr).
M. Beşkirli and H. Uğuz are with the Computer Engineering Department, Selcuk University, Konya, Turkey.
H. Haklı is with the Computer Engineering Department, Necmettin Erbakan University, Konya, Turkey.

[PDF]

Cite:Ayşe Beşkirli, Mehmet Beşkirli, Hüseyin Haklı, and Harun Uğuz, "Comparing Energy Demand Estimation Using Artificial Algae Algorithm: The Case of Turkey," Journal of Clean Energy Technologies vol. 6, no. 4, pp. 349-352, 2018.

Copyright © 2008-2016. Journal of Clean Energy Technologies. All rights reserved.
E-mail: jocet@ejournal.net