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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
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2021-Jun-06
SCOPUS published the CiteScore for 2020, computed by using an improved methodology, counting the citations received in 2017-2020 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering in 2020 is 2.5, better than all our previous results.

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  2/2020 - 4

 HIGHLY CITED PAPER 

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: 525 | Views: 1,061

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.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 6
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Cited-By CrossRef

[1] A new modified artificial bee colony algorithm for energy demand forecasting problem, Özdemir, Durmuş, Dörterler, Safa, Aydın, Doğan, Neural Computing and Applications, ISSN 0941-0643, Issue 20, Volume 34, 2022.
Digital Object Identifier: 10.1007/s00521-022-07675-7
[CrossRef]

[2] Multi-objective optimal allocation of regional water resources based on slime mould algorithm, Wu, Xian, Wang, Zhaocai, The Journal of Supercomputing, ISSN 0920-8542, 2022.
Digital Object Identifier: 10.1007/s11227-022-04599-w
[CrossRef]

[3] Realization of Turkey’s energy demand forecast with the improved arithmetic optimization algorithm, Aslan, Murat, Beşkirli, Mehmet, Energy Reports, ISSN 2352-4847, Issue , 2022.
Digital Object Identifier: 10.1016/j.egyr.2022.06.101
[CrossRef]

[4] Solving continuous optimization problems using the tree seed algorithm developed with the roulette wheel strategy, Beşkirli, Mehmet, Expert Systems with Applications, ISSN 0957-4174, Issue , 2021.
Digital Object Identifier: 10.1016/j.eswa.2021.114579
[CrossRef]

[5] A novel Invasive Weed Optimization with levy flight for optimization problems: The case of forecasting energy demand, Beşkirli, Mehmet, Energy Reports, ISSN 2352-4847, Issue , 2022.
Digital Object Identifier: 10.1016/j.egyr.2021.11.108
[CrossRef]

[6] Gradyan Tabanlı Optimize Edici Algoritmasının Parametre Ayarlaması, BEŞKİRLİ, Mehmet, TEFEK, Mehmet Fatih, European Journal of Science and Technology, ISSN 2148-2683, 2021.
Digital Object Identifier: 10.31590/ejosat.1010813
[CrossRef]

[7] Optimization of PV and Battery Energy Storage Size in Grid-Connected Microgrid, Garip, Selahattin, Ozdemir, Saban, Applied Sciences, ISSN 2076-3417, Issue 16, Volume 12, 2022.
Digital Object Identifier: 10.3390/app12168247
[CrossRef]

Updated 2 days, 3 hours ago

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