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JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Nov 2020
Next issue: Feb 2021
Avg review time: 56 days


PUBLISHER

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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  2/2017 - 10

 HIGH-IMPACT PAPER 

Golden Sine Algorithm: A Novel Math-Inspired Algorithm

TANYILDIZI, E. See more information about TANYILDIZI, E. on SCOPUS See more information about TANYILDIZI, E. on IEEExplore See more information about TANYILDIZI, E. on Web of Science, DEMIR, G. See more information about DEMIR, G. on SCOPUS See more information about DEMIR, G. on SCOPUS See more information about DEMIR, G. on Web of Science
 
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Download PDF pdficon (1,408 KB) | Citation | Downloads: 949 | Views: 2,545

Author keywords
artificial intelligence, computational intelligence, evolutionary computation, heuristic algorithms, optimization

References keywords
optimization(24), algorithm(14), algorithms(7), inspired(5), computation(5), yang(4), swarm(4), software(4), jadvengsoft(4), evolutionary(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 71 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02010
Web of Science Accession Number: 000405378100010
SCOPUS ID: 85020089767

Abstract
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In this study, Golden Sine Algorithm (Gold-SA) is presented as a new metaheuristic method for solving optimization problems. Gold-SA has been developed as a new search algorithm based on population. This math-based algorithm is inspired by sine that is a trigonometric function. In the algorithm, random individuals are created as many as the number of search agents with uniform distribution for each dimension. The Gold-SA operator searches to achieve a better solution in each iteration by trying to bring the current situation closer to the target value. The solution space is narrowed by the golden section so that the areas that are supposed to give only good results are scanned instead of the whole solution space scan. In the tests performed, it is seen that Gold-SA has better results than other population based methods. In addition, Gold-SA has fewer algorithm-dependent parameters and operators than other metaheuristic methods, increasing the importance of this method by providing faster convergence of this new method.


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Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 13
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Cited-By CrossRef

[1] Geliştirilmiş Adaptif Sinüs Kosinüs Algoritması (ASKA)’nın Optimizasyon Problemlerinin Çözümünde Kullanılması, TANYILDIZI, Erkan, DEMİR, Gökhan, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, ISSN 1308-9072, Issue 2, Volume 30, 2018.
Digital Object Identifier: 10.35234/fumbd.461542
[CrossRef]

[2] Extreme Learning Machine Soft-Sensor Model With Different Activation Functions on Grinding Process Optimized by Improved Black Hole Algorithm, Xie, W., Wang, J. S., Xing, C., Guo, S. S., Guo, M. W., Zhu, L. F., IEEE Access, ISSN 2169-3536, Issue , 2020.
Digital Object Identifier: 10.1109/ACCESS.2020.2970429
[CrossRef]

[3] Impacts of Linnik Flight Usage Patterns on Cuckoo Search for Real-Parameter Global Optimization Problems, Nasa-Ngium, Patchara, Sunat, Khamron, Chiewchanwattana, Sirapat, IEEE Access, ISSN 2169-3536, Issue , 2019.
Digital Object Identifier: 10.1109/ACCESS.2019.2923557
[CrossRef]

[4] Improved Black Hole Algorithm Based on Golden Sine Operator and Levy Flight Operator, Xie, W., Wang, J. S., Tao, Y., IEEE Access, ISSN 2169-3536, Issue , 2019.
Digital Object Identifier: 10.1109/ACCESS.2019.2951716
[CrossRef]

[5] Improved Whale Optimization Algorithm Based on Nonlinear Adaptive Weight and Golden Sine Operator, Zhang, J., Wang, J. S., IEEE Access, ISSN 2169-3536, Issue , 2020.
Digital Object Identifier: 10.1109/ACCESS.2020.2989445
[CrossRef]

[6] Grasshopper optimization algorithm tuned maximum power point tracking for solar photovoltaic systems, Subramanian, Annapoorani, Raman, Jayaparvathy, Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, 2020.
Digital Object Identifier: 10.1007/s12652-020-02593-9
[CrossRef]

[7] Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations, Molina, Daniel, Poyatos, Javier, Ser, Javier Del, García, Salvador, Hussain, Amir, Herrera, Francisco, Cognitive Computation, ISSN 1866-9956, Issue 5, Volume 12, 2020.
Digital Object Identifier: 10.1007/s12559-020-09730-8
[CrossRef]

[8] Hybrid Henry Gas Solubility Optimization Algorithm Based on the Harris Hawk Optimization, Xie, Wei, Xing, Cheng, Wang, Jiesheng, Guo, Shasha, Guo, Meng-Wei, Zhu, Ling-Feng, IEEE Access, ISSN 2169-3536, Issue , 2020.
Digital Object Identifier: 10.1109/ACCESS.2020.3014309
[CrossRef]

[9] Güncel Metasezgisel Optimizasyon Algoritmalarının Performans Karşılaştırılması, EROZ, Eyup, TANYILDIZI, Erkan, 2018 International Conference on Artificial Intelligence and Data Processing (IDAP), ISBN 978-1-5386-6878-8, 2018.
Digital Object Identifier: 10.1109/IDAP.2018.8620764
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
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