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Article:Data Clustering using almost parameter free Differential Evolution technique

by Sai Hanuman A, Dr Vinaya Babu A, Dr Govardhan A, Dr S C Satapathy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 13
Year of Publication: 2010
Authors: Sai Hanuman A, Dr Vinaya Babu A, Dr Govardhan A, Dr S C Satapathy
10.5120/1310-1811

Sai Hanuman A, Dr Vinaya Babu A, Dr Govardhan A, Dr S C Satapathy . Article:Data Clustering using almost parameter free Differential Evolution technique. International Journal of Computer Applications. 8, 13 ( October 2010), 1-7. DOI=10.5120/1310-1811

@article{ 10.5120/1310-1811,
author = { Sai Hanuman A, Dr Vinaya Babu A, Dr Govardhan A, Dr S C Satapathy },
title = { Article:Data Clustering using almost parameter free Differential Evolution technique },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 13 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number13/1310-1811/ },
doi = { 10.5120/1310-1811 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:15.259667+05:30
%A Sai Hanuman A
%A Dr Vinaya Babu A
%A Dr Govardhan A
%A Dr S C Satapathy
%T Article:Data Clustering using almost parameter free Differential Evolution technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 13
%P 1-7
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper presents a comparative analysis of data clustering by Particle swarm optimization (PSO) and differential evolution (DE) techniques. It is clearly reveled from the simulation results that almost parameter free optimization technique such as Differential evolution could provide better performance compared to PSO where in many parameters are to be tuned. To exhibit the numerical optimizing capability of DE we have demonstrated the capability of this by optimizing few benchmark functions.

References
  1. R. C. Eberhart, and Y. Shi. Particle swarm optimization: developments, applications and resources. Proceedings of the IEEE congress on evolutionary computation. 2001.
  2. R. Poli, J. Kennedy, and T. Blackwell. Particle Swarm Optimization: An overview. Swarm Intelligence. July, 2007.
  3. A. Banks, J. Vincent, and C. Anyakoha. A review of particle swarm optimization, part 1: Background and Development. Nat Comput. 2007.
  4. Y. Shi. Particle swarm optimization. IEEE Neural network society. February, 2004.
  5. Y. Shi, and R. C. Eberhart. Empirical study of particle swarm optimization. IEEE. 1999.
  6. Storn R and Price K (1997), Differential Evolution – A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces, Journal of Global Optimization, 11(4), 341–359..
  7. S. Das, A. Abraham, and A. Konar. Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives. Studies in Computational Intelligence (SCI) 116, 1-38, 2008.
  8. A. K. Jain, M. N. Murthy, and P. J. Flynn. Data clustering: a review. ACM Computing surveys, Volume 31, No. 3. September, 1999.
  9. S. Das, and A. Abraham. Automatic clustering using an improved differential evolution algorithm. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and Humans, Volume 38, No. 1, January, 2008.
  10. Kennedy JF, Eberhart RC. Particle swarm optimization. In: Proceedings of the IEEE International conference on neural networks, vol. 4. Perth, Australia; p. 1942–48,1995.
  11. Shi Y and Eberhart RC ,Parameter Selection in Particle Swarm Optimization, Evolutionary Programming VII, Springer, Lecture Notes in Computer Science 1447, 591–600, (1998).
  12. Kenneth D. Bailey, Cluster Analysis. Sociological Methodology, Vol. 6 pp. 59-128, American Sociological Association, 1975.
  13. Oded Z. Maimon, Lior Rokach, The Data Mining and Knowledge Discovery Handbook, Springer Science & Business, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Data Clustering PSO Differential evolution Function Optimization

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