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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 104 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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FEATURED ARTICLE

ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection, SARACOGLU, O. G., BAGIS, A., KONAR, M., TABARU, T. E.
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LATEST NEWS

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-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

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.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
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.

Read More »


    
 

  4/2010 - 13

Genetic Algorithm-based Dynamic Vehicle Route Search using Car-to-Car Communication

OH, B. See more information about OH, B. on SCOPUS See more information about OH, B. on IEEExplore See more information about OH, B. on Web of Science, NA, Y. See more information about  NA, Y. on SCOPUS See more information about  NA, Y. on SCOPUS See more information about NA, Y. on Web of Science, YANG, J. See more information about  YANG, J. on SCOPUS See more information about  YANG, J. on SCOPUS See more information about YANG, J. on Web of Science, PARK, S. See more information about  PARK, S. on SCOPUS See more information about  PARK, S. on SCOPUS See more information about PARK, S. on Web of Science, NANG, J. See more information about  NANG, J. on SCOPUS See more information about  NANG, J. on SCOPUS See more information about NANG, J. on Web of Science, KIM, J. See more information about KIM, J. on SCOPUS See more information about KIM, J. on SCOPUS See more information about KIM, J. 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 (4,747 KB) | Citation | Downloads: 1,343 | Views: 2,719

Author keywords
adaptive system, genetic algorithm, traffic information system

References keywords
genetic(10), algorithm(6), routing(5), problem(4), learning(4), algorithms(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-11-30
Volume 10, Issue 4, Year 2010, On page(s): 81 - 86
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.04013
Web of Science Accession Number: 000284782700013
SCOPUS ID: 78649707649

Abstract
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Full text preview
Suggesting more efficient driving routes generate benefits not only for individuals by saving commute time, but also for society as a whole by reducing accident rates and social costs by lessening traffic congestion. In this paper, we suggest a new route search algorithm based on a genetic algorithm which is more easily installable into mutually communicating car navigation systems, and validate its usefulness through experiments reflecting real-world situations. The proposed algorithm is capable of searching alternative routes dynamically in unexpected events of system malfunctioning or traffic slow-downs due to accidents. Experimental results demonstrate that our algorithm searches the best route more efficiently and evolves with universal adaptability.


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

[1] Explanation of Transport Protocol Experts Group, Dec. 2, 2008, Available: Temporary on-line reference link removed - see the PDF document

[2] E. Moon, "The Introduction of Digital Multimedia Broadcasting in Korea," July 2006, Available: Temporary on-line reference link removed - see the PDF document

[3] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Upper Saddle River, NJ: Addison-Wesley, 1989.

[4] C. W. Ahn, R. S. Ramakrishna, and C. G. Kang, "A New Genetic Algorithm for Shortest Path Routing Problem," IEEE Transactions on Evolutionary Computation, Vol. 6, No. 6, Dec. 2002.

[5] J. Pearl, Heuristics: Intelligent Search Strategies for Computer Problem Solving. Upper Saddle River, NJ: Addison-Wesley, 1984.

[6] A. Nagurney and Q. Qiang, "Robustness of transportation networks subject to degradable links," A Letters Journal Exploring the Frontiers of Physics, 68001-p1-p6, 2007.

[7] I. H. Jung, D. H. Son, "Survey of Highway Business Effect," Korea Research Institute for Human Settlements, 1995.

[8] E. W. Dijkstra, "A Note on Two Problems in Connexion with Graphs," Numerische Mathematik, Vol. 1, pp. 269-271, 1959.
[CrossRef] [SCOPUS Times Cited 9770]


[9] Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA, 1998.

[10] G. Harik, E. Cant¢u-Paz, D. E. Goldberg, and B. L. Miller, "The Gambler's ruin problem, genetic algorithms, and the sizing of populations," Evol. Comput., Vol. 7, No. 3, pp. 231-253, 1999.
[CrossRef] [PubMed] [Web of Science Times Cited 148]


[11] M. Munetomo, Y. Takai, and Y. Sato, "A Migration Scheme for the Genetic Adaptive Routing Algorithm," IEEE International Conference on Systems, Man, and Cybernetics, pp. 2774-2779, 1998.
[CrossRef]


[12] J. Inagaki, M. Haseyama, and H. Kitajima, "A Genetic Algorithm for Determining Multiple Route and Its Applications," Proceedings of IEEE International Symposium on Circuits and Systems, pp. 137-140, 1999.
[CrossRef]


[13] Y. Leung, G. Li, and Z. B. Xu, "A genetic algorithm for the multiple destination routing problems," IEEE Trans. EVol. Comput., Vol. 2, pp. 150-161, Nov. 1998.
[CrossRef] [SCOPUS Times Cited 82]


[14] Z. Xiawei, C. Changjia, and Z. Gang, "A genetic algorithm for multicasting routing problem," in Proc. Int. Conf. Communication Technology (WCC-ICCT 2000), pp. 1248-1253, 2000.

[15] N. Shimamoto, A. Hiramatsu, and K. Yamasaki, "A dynamic routing control based on a genetic algorithm," in Proc. IEEE Int. Conf. Neural Networks, pp. 1123-1128, 1993.
[CrossRef] [SCOPUS Times Cited 51]


[16] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley.

[17] X. Hue, "Genetic algorithms for optimization: Background and applications," Edinburgh Parallel Computing Centre, Univ. Edinburgh, Edinburgh, Scotland, Ver 1.0, Feb. 1997.

[18] Sebastian Zander, Thuy Nguyen, and Grenville Armitage, "Automated traffic classification and application identification using machine learning," in Proc. of IEEE Conf. on Local Computer Networks, pp. 250-257, 2005.
[CrossRef] [SCOPUS Times Cited 261]




References Weight

Web of Science® Citations for all references: 148 TCR
SCOPUS® Citations for all references: 10,164 TCR

Web of Science® Average Citations per reference: 8 ACR
SCOPUS® Average Citations per reference: 535 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 2017-11-20 00:44 in 93 seconds.




Note1: Web of Science® is a registered trademark of Thomson Reuters.
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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