Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 0.459
JCR 5-Year IF: 0.442
Issues per year: 4
Current issue: Nov 2016
Next issue: Feb 2017
Avg review time: 74 days


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

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


1,531,941 unique visits
Since November 1, 2009

No robots online now


SCImago Journal & Country Rank

SEARCH ENGINES - Google Pagerank


Anycast DNS Hosting

 Volume 16 (2016)
     »   Issue 4 / 2016
     »   Issue 3 / 2016
     »   Issue 2 / 2016
     »   Issue 1 / 2016
 Volume 15 (2015)
     »   Issue 4 / 2015
     »   Issue 3 / 2015
     »   Issue 2 / 2015
     »   Issue 1 / 2015
 Volume 14 (2014)
     »   Issue 4 / 2014
     »   Issue 3 / 2014
     »   Issue 2 / 2014
     »   Issue 1 / 2014
 Volume 13 (2013)
     »   Issue 4 / 2013
     »   Issue 3 / 2013
     »   Issue 2 / 2013
     »   Issue 1 / 2013
  View all issues  


Broken Bar Fault Detection in IM Operating Under No-Load Condition, RELJIC, D., JERKAN, D., MARCETIC, D., OROS, D.
Issue 4/2016



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 "Big Data - " before the paper title in OpenConf.

We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

Thomson Reuters published the Journal Citations Report for 2015. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.459, and the JCR 5-Year Impact Factor is 0.442.

Starting with Issue 2/2016, the article processing charge is 300 EUR for each article accepted for publication. The charge of 25 EUR per page for papers over 8 pages will not be changed. Details are available in the For authors section.

Read More »


  2/2015 - 7

Incorporating the Avoidance Behavior to the Standard Particle Swarm Optimization 2011

ALTINOZ, O. T. See more information about ALTINOZ, O. T. on SCOPUS See more information about ALTINOZ, O. T. on IEEExplore See more information about ALTINOZ, O. T. on Web of Science, YILMAZ, A. E. See more information about  YILMAZ, A. E. on SCOPUS See more information about  YILMAZ, A. E. on SCOPUS See more information about YILMAZ, A. E. on Web of Science, DUCA, A. See more information about  DUCA, A. on SCOPUS See more information about  DUCA, A. on SCOPUS See more information about DUCA, A. on Web of Science, CIUPRINA, G. See more information about CIUPRINA, G. on SCOPUS See more information about CIUPRINA, G. on SCOPUS See more information about CIUPRINA, G. on Web of Science
Click to see author's profile on 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 (785 KB) | Citation | Downloads: 186 | Views: 1,004

Author keywords
particle swarm optimization, social factors, cognitive informatics, performance evaluation

References keywords
swarm(14), optimization(14), systems(5), evolutionary(5), computation(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 51 - 58
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02007
Web of Science Accession Number: 000356808900007
SCOPUS ID: 84979834398

Quick view
Full text preview
Inspired from social and cognitive behaviors of animals living as swarms; particle swarm optimization (PSO) provides a simple but very powerful tool for researchers who are dealing with collective intelligence. The algorithm depends on modeling the very basic random behavior (i.e. exploration capability) of individuals in addition to their tendency to revisit positions of good memories (cognitive behavior) and tendency to keep an eye on and follow the majority of swarm members (social behavior). The balance among these three major behaviors is the key of success of the algorithm. On the other hand, there are other social and cognitive phenomena, which might be useful for improvement of the algorithm. In this paper, we particularly investigate avoidance from the bad behavior. We propose modifications about modeling the Standard PSO 2011 formulation, and we test performance of our proposals at each step via benchmark functions, and compare the results of the proposed algorithms with well-known algorithms. Our results show that incorporation of Social Avoidance behavior into SPSO11 improves the performance. It is also shown that in case the Social Avoidance behavior is applied in an adaptive manner at the very first iterations of the algorithm, there might be further improvements.

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

[1] G. Beni, J. Wang, "Swarm intelligence in cellular robotic systems," NATO Advanced Workshop on Robots and Biological Systems, Tuscany, Italy, 1989.

[2] M. Dorigo, "Optimization, learning and natural algorithms (in Italian)," Ph.D. Thesis, Politecnico di Milano, Italy, 1992.

[3] M. Dorigo, G. DiCaro and L.M. Gambardella, "Ant algorithms for discrete optimization," Artificial Life, vol. 5, no. 2, pp. 137-172, 1999.
[CrossRef] [Web of Science Times Cited 1184]

[4] J. Kennedy, R. Eberhart, "Particle swarm optimization," IEEE International Conference on Neural Networks, pp. 1942-1948, 1995.
[CrossRef] [Web of Science Times Cited 16636] [SCOPUS Record]

[5] G. Bilchev, I. C. Parmee, "The ant colony metaphor for searching continuous design spaces," AISB Workshop on Evolutionary Computation, vol. 993, pp. 25-39, 1995.
[CrossRef] [SCOPUS Times Cited 145]

[6] N. Monmarché, G. Venturini, M. Slimane, "On how pachycondyla apicalis ants suggest a new search algorithm," Future Generation Computer Systems, vol. 16, no. 8, pp. 937-946, 2000.
[CrossRef] [Web of Science Times Cited 134] [SCOPUS Times Cited 175]

[7] J. Dréo, P. Siarry, "A new ant colony algorithm using the hierarchical concept aimed at optimization of multi minima continuous functions," 3rd International Workshop on Ant Algorithms (ANTS’2002), vol. 2463, pp. 216-221, 2002.

[8] J. Kennedy, R. C. Eberhart, "Discrete binary version of the particle swarm algorithm," IEEE International Conference on Systems, Man, and Cybernetics, pp. 4104-4108, 1997.

[9] M. Clerc, "The swarm and the queen: towards a deterministic and adaptive particle swarm optimization," Congress on Evolutionary Computation, pp. 1951-1957, 1999.
[CrossRef] [SCOPUS Times Cited 846]

[10] C. K. Mohan, B. Al-kazemi, "Discrete particle swarm optimization," Workshop on Particle Swarm Optimization, Purdue School of Engineering and Technology, Indianapolis, IN, 2001.

[11] J. Robinson, Y. Rahmat-Samii, "Particle swarm optimization in electromagnetics," IEEE Transactions on Antennas and Propagation vol. 52, no. 2, pp. 397-407, 2004.
[CrossRef] [Web of Science Times Cited 854] [SCOPUS Times Cited 1269]

[12] P. Poli, "Analysis of the publications on the applications of particle swarm optimization," Journal of Artificial Evolution and Applications, Article ID: 685175, 2008.

[13] M. Zambrano-Bigiarini, M. Clerc, R. Rojas, "Standard Particle Swarm Optimisation 2011 at CEC-2013: A baseline for future PSO improvements," IEEE Congress on Evolutionary Computation (CEC), pp. 2337 - 2344, 2013.
[CrossRef] [SCOPUS Times Cited 52]

[14] C. Yang, D. Simon, "A new particle swarm optimization technique," 18th International Conference on Systems Engineering, pp. 164-169, 2005.
[CrossRef] [SCOPUS Times Cited 34]

[15] G. Ciuprina, D. Ioan, I. Munteanu, "Use of intelligent-particle swarm optimization in electromagnetics," IEEE Transactions on Magnetics, vol. 38, no. 2, pp. 1037-1040, 2002.
[CrossRef] [Web of Science Times Cited 144] [SCOPUS Times Cited 224]

[16] O.T.Altinoz, A.E.Yilmaz and G.Ciuprina, "Use of Karczmarz’s method in Intelligent-Particle Swarm Optimization", International Conference on Electrical and Electronics Engineering, pp. 526-530, Bursa, 2013.

[17] A. Biswas, A. Kumar, K.K. Mishra, "Particle Swarm Optimization with cognitive avoidance component," International Conf. on Advances in Computer, Communication and Informatics, pp. 149 - 154, 2013.
[CrossRef] [SCOPUS Times Cited 3]

[18] J.J. Liang, P.N. Suganthan and K. Deb, "Novel Composition Test Functions for Numerical Global Optimization," IEEE Congress on Evolutionary Computation, pp. 68-75, 2005. Matlab codes of benchmark problems: index_files/

[19] F.C. Lam, M.T. Longnecker, "A modified Wilcoxon rank sum test for paired data," Biometrika, vol. 70, no. 2, pp. 510-513, 1983.
[CrossRef] [SCOPUS Times Cited 45]

[20] C. K. Monson and K. D. Seppi, "Exposing Origin-Seeking Bias in PSO," Genetic and Evolutionary Computation Conference GECCO, pp. 241-248, 2005.
[CrossRef] [SCOPUS Times Cited 33]

References Weight

Web of Science® Citations for all references: 18,952 TCR
SCOPUS® Citations for all references: 2,826 TCR

Web of Science® Average Citations per reference: 902 ACR
SCOPUS® Average Citations per reference: 135 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 background updated on 2017-02-25 11:23 in 114 seconds.

Note1: Web of Science® is a registered trademark of Thomson Reuters.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2017
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.

Website loading speed and performance optimization powered by: