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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  2/2020 - 4

Determination with Linear Form of Turkey's Energy Demand Forecasting by the Tree Seed Algorithm and the Modified Tree Seed Algorithm

BESKIRLI, A. See more information about BESKIRLI, A. on SCOPUS See more information about BESKIRLI, A. on IEEExplore See more information about BESKIRLI, A. on Web of Science, TEMURTAS, H. See more information about  TEMURTAS, H. on SCOPUS See more information about  TEMURTAS, H. on SCOPUS See more information about TEMURTAS, H. on Web of Science, OZDEMIR, D. See more information about OZDEMIR, D. on SCOPUS See more information about OZDEMIR, D. on SCOPUS See more information about OZDEMIR, D. on Web of Science
 
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Download PDF pdficon (1,422 KB) | Citation | Downloads: 152 | Views: 257

Author keywords
algorithms, demand forecasting, energy optimization, heuristic algorithms

References keywords
energy(45), demand(19), turkey(17), algorithm(17), optimization(13), systems(8), artificial(8), forecasting(7), applications(7), neural(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2020-05-31
Volume 20, Issue 2, Year 2020, On page(s): 27 - 34
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.02004
Web of Science Accession Number: 000537943500004
SCOPUS ID: 85087464201

Abstract
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Energy plays an important role in every stage of human life in different forms and variations. Along with the developments in economic, social and industrial fields, the amount of energy that countries need is increasing day by day. Therefore, it is significant to estimate the energy demand for a country's economic activities accurately. In this study, the energy demand forecast (EDF) application optimization problem of Turkey, one of the real-world optimization problems, was performed by MTSA (Modified Tree Seed Algorithm) and TSA (Tree Seed Algorithm) methods. From 1979 to 2005, gross domestic product (GDP), population, export and import values were used as parameter data. Thus, in the presence of three different possible scenarios, Turkey's energy demand from 2006 to 2025, which was estimated by MTSA and TSA methods. To demonstrate the success of MTSA and TSA in the problem of energy demand forecasting (EDF), they are compared with Ant Colony Algorithm (ACO), Particle Swarm Optimization (PSO), Bat Algorithm (BA), Differential Evolution Algorithm (DEA) and Artificial Algae Algorithm (AAA) methods which are in the literature. According to the results of the analysis, it was observed that the MTSA method was a successful estimation tool for energy demand.


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References Weight

Web of Science® Citations for all references: 2,652 TCR
SCOPUS® Citations for all references: 3,165 TCR

Web of Science® Average Citations per reference: 56 ACR
SCOPUS® Average Citations per reference: 67 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-10-21 02:57 in 243 seconds.




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