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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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2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  4/2018 - 6

Continuous Time Chaotic Systems for Whale Optimization 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, CIGAL, T. See more information about CIGAL, T. on SCOPUS See more information about CIGAL, T. on SCOPUS See more information about CIGAL, T. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,307 KB) | Citation | Downloads: 100 | Views: 99

Author keywords
artificial intelligence, chaos, computational intelligence, continuous time systems, whale optimization algorithm

References keywords
optimization(23), algorithm(12), chaos(11), chaotic(9), algorithms(9), systems(6), evolutionary(6), swarm(5), computation(5), applied(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 49 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04006
Web of Science Accession Number: 000451843400006
SCOPUS ID: 85058817066

Abstract
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Discrete time chaotic systems are often used instead of random number arrays in order to improve the convergence properties of optimization algorithms and prevent them to get stuck on local solutions. In this study, discrete-time and continuous-time chaotic systems are employed to improve the performance of Whale Optimization Algorithm (WOA), for the first time. It is suggested to use continuous-time chaotic systems instead of discrete-time systems in some cases. Using 23 benchmark functions and two engineering problems, one-dimensional chaotic maps and continuous time chaotic systems were analyzed on WOA. The results show that especially in multidimensional problems the use of the continuous time chaotic system can improve the performance of the algorithm and provide faster convergence.


References | Cited By  «-- Click to see who has cited this paper

[1] B. Alatas, "Chaotic bee colony algorithms for global numerical optimization", Expert Systems with Applications, vol. 37, no. 8, pp. 5682-5687, 2010.
[CrossRef] [Web of Science Times Cited 221] [SCOPUS Times Cited 293]


[2] X. Yang, S. Deb, "Engineering optimization by cuckoo search" International Journal of Mathematical Modelling and Numerical Optimization, vol. 1, no. 4, pp. 330-343, 2010.
[CrossRef] [SCOPUS Times Cited 1148]


[3] R. Eberhart, J. Kennedy. "A new optimizer using particle swarm theory", Micro Machine and Human Science, MHS'95., Proceedings of the Sixth International Symposium, pp. 39-43, 1995.
[CrossRef]


[4] M. Dorigo, M. Birattari, T. Stutzle. "Ant colony optimization", IEEE computational intelligence magazine, vol. 1, no.4, pp.28-39, 2006.
[CrossRef] [Web of Science Times Cited 873] [SCOPUS Times Cited 1186]


[5] K. F. Man, K. S. Tang, S.Kwong. "Genetic algorithms: concepts and applications [in engineering design]", IEEE transactions on Industrial Electronics, vol. 43, no. 5, pp. 519-534, 1996.
[CrossRef] [Web of Science Times Cited 509] [SCOPUS Times Cited 696]


[6] D. Karaboga, B. Basturk, "Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems", Foundations of fuzzy logic and soft computing, pp. 789-798, 2007.
[CrossRef]


[7] E. Tanyildizi, G. Demir, "Golden Sine Algorithm, A Novel Math-Inspired Algorithm", Advances in Electrical and Computer Engineering, vol. 17, no. 2, pp. 71-78, 2017.
[CrossRef] [Web of Science Times Cited 203] [SCOPUS Times Cited 278]


[8] H. Joshi, S. Arora, "Enhanced grey wolf optimization algorithm for global optimization", Fundamenta Informaticae, vol. 153 no.3, pp.235-264, 2017.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]


[9] S. Mirjalili, A. Lewis, "The Whale Optimization Algorithm", Advances in Engineering Software, vol. 95, pp.51-67, 2016.
[CrossRef] [Web of Science Times Cited 279] [SCOPUS Times Cited 420]


[10] S. Mirjalili S., Mirjalili S. M., Lewis A. "Grey wolf optimizer", Advances in engineering software, vol. 69, pp.46-61, 2014.
[CrossRef] [Web of Science Times Cited 858] [SCOPUS Times Cited 1201]


[11] N. Jayakumar, S. Subramanian, S. Ganesan, E.B. Elanchezhian, "Grey wolf optimization for combined heat and power dispatch with cogeneration systems", International Journal of Electrical Power & Energy Systems, vol.74, pp.252-264, 2016.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 42]


[12] R. E. Precup, R. C. David, E. M. Petriu, "Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity", IEEE Transactions on Industrial Electronics, vol. 64 no.1, pp.527-534, 2017.
[CrossRef] [Web of Science Times Cited 38] [SCOPUS Times Cited 47]


[13] L. Dos Santos Coelho, D. L. de Andrade Bernert, V. C. Mariani, "A chaotic firefly algorithm applied to reliability-redundancy optimization", Evolutionary Computation (CEC), IEEE Congress, pp. 517-521, 2011.
[CrossRef] [SCOPUS Times Cited 66]


[14] B. Alatas, E. Akin, B. Ozer, "Chaos embedded particle swarm optimization algorithms", Chaos, Solitons & Fractals,vol. 40, no. 4, pp.1715-1734, 2009.
[CrossRef] [Web of Science Times Cited 203] [SCOPUS Times Cited 278]


[15] L. S. Coelho, V. C. Mariani, "Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization", Expert Systems with Applications, vol. 34, pp. 1905-1913, 2008.
[CrossRef] [Web of Science Times Cited 77] [SCOPUS Times Cited 94]


[16] L. Y. Chuang, C. H. Yang, J. C. Li, "Chaotic maps based on binary particle swarm optimization for feature selection", Applied Soft Computing, vol. 11, no. 1, pp. 239-248,2011.
[CrossRef] [Web of Science Times Cited 85] [SCOPUS Times Cited 102]


[17] Sayed G. I., Darwish A., Hassanien A. E. "A New Chaotic Whale Optimization Algorithm for Features Selection", Journal of Classification, vol. 35, pp. 1-45, 2018.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]


[18] E. Tanyildizi, T. Cigal, "Whale Optimization Algorithms with Chaotic Mapping", Firat University, Engineering Sciences Journal, vol. 29 , no. 1, pp. 307-317, 2017.

[19] F. Ozkaynak, "A novel method to improve the performance of chaos based evolutionary algorithms", Optik-International Journal for Light and Electron Optics, vol. 126, no.24, pp. 5434-5438, 2015.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 11]


[20] Hala S., Hamilton H. J., Domenici P., "Simulating the Bubble Net Hunting Behaviour of Humpback Whales: The BNH-Whale Algorithm", Canadian Conference on Artificial Intelligence, Springer, Cham, pp.40-45, 2016.
[CrossRef]


[21] R. Caponetto, L. Fortuna, S. Fazzino, M. G. Xibilia, "Chaotic sequences to improve the performance of evolutionary algorithms", IEEE transactions on evolutionary computation, vol. 7, no.3, pp. 289-304, 2003.
[CrossRef] [Web of Science Times Cited 280] [SCOPUS Times Cited 370]


[22] H. Nozawa, "A neural network model as a globally coupled map and applications based on chaos", Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 2, no. 3, pp. 377-386, 1992.
[CrossRef] [Web of Science Times Cited 205] [SCOPUS Times Cited 217]


[23] K. Fallahi, R. Raoufi, H. Khoshbin, "An application of Chen system for secure chaotic communication based on extended Kalman filter and multi-shift cipher algorithm", Communications in Nonlinear Science and Numerical Simulation, vol. 13, no. 4, pp. 763-781, 2008.
[CrossRef] [Web of Science Times Cited 42] [SCOPUS Times Cited 49]


[24] L. O. Chua, C. W. Wu, A. Huang, G. Q. Zhong, "A universal circuit for studying and generating chaos", I. Routes to chaos. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 40, no. 10, pp. 732-744, 1993.
[CrossRef] [Web of Science Times Cited 300] [SCOPUS Times Cited 346]


[25] T. Matsumoto, "Chaos in electronic circuits", Proceedings of the IEEE, vol. 75, no.8, pp.1033-1057, 1987.
[CrossRef] [Web of Science Times Cited 79] [SCOPUS Times Cited 91]


[26] M. S. Tavazoei, M. Haeri, "Comparison of different one-dimensional maps as chaotic search pattern in chaos optimization algorithms", Applied Mathematics and Computation, vol. 187, no. 2, pp. 1076-1085, 2007.
[CrossRef] [Web of Science Times Cited 115] [SCOPUS Times Cited 140]


[27] D. Yang, G. Li, G. Cheng, "On the efficiency of chaos optimization algorithms for global optimization", Chaos, Solitons & Fractals, vol. 34, no. 4, pp. 1366-1375, 2007.
[CrossRef] [Web of Science Times Cited 124] [SCOPUS Times Cited 164]


[28] E. N. Lorenz, "Deterministic nonperiodic flow", Journal of the atmospheric sciences, vol. 20, no. 2, pp. 130-141, 1963.
[CrossRef]


[29] X. Yao, Y. Liu, G. Lin, "Evolutionary programming made faster", IEEE Transactions on Evolutionary computation, vol. 3, no. 2, pp. 82-102, 1999.
[CrossRef] [Web of Science Times Cited 1759] [SCOPUS Times Cited 2250]


[30] C. Worasucheep, "Solving constrained engineering optimization problems by the constrained PSO-DD", In Electrical Engineering/Electronics, Computer, Information Technology and Telecommunications. ECTI-CON. 5th International Conference, Vol. 1, pp. 5-8, 2008.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 12]


[31] S. Hassan, K. Kumar, C. D. Raj, K. Sridhar, "Design and optimization of pressure vessel using metaheuristic approach", Applied Mechanics and Materials, Trans Tech Publications, vol. 465, pp. 401-406, 2014.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 3]


[32] X. Hu, R. C. Eberhart, Y. Shi, "Engineering optimization with particle swarm", Swarm Intelligence Symposium, 2003. SIS'03. Proceedings of the 2003 IEEE, pp. 53-57, 2003.
[CrossRef] [Web of Science Times Cited 151] [SCOPUS Times Cited 269]


[33] C. A. C. Coello, E. M. Montes, "Constraint-handling in genetic algorithms through the use of dominance-based tournament selection", Advanced Engineering Informatics, vol. 16, no. 3, pp. 193-203.
[CrossRef] [Web of Science Times Cited 300] [SCOPUS Times Cited 382]


[34] [Online] Available: Temporary on-line reference link removed - see the PDF document

[35] M. Mahdavi, M. Fesanghary, E. Damangir, "An improved harmony search algorithm for solving optimization problems", Applied mathematics and computation, vol. 188, no. 2, pp. 1567-1579, 2007.
[CrossRef] [Web of Science Times Cited 750] [SCOPUS Times Cited 1121]




References Weight

Web of Science® Citations for all references: 7,521 TCR
SCOPUS® Citations for all references: 11,284 TCR

Web of Science® Average Citations per reference: 209 ACR
SCOPUS® Average Citations per reference: 313 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 2019-01-20 13:55 in 234 seconds.




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