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A Kernel Based Clustering Algorithm using Particle Swarm Optimization Cover

A Kernel Based Clustering Algorithm using Particle Swarm Optimization

Annals of West University of Timisoara - Mathematics and Computer Science
Volume 51 (2013): Issue 1 (June 2013)
By:  and    
Open Access
|Aug 2013
References

References

  1. [1] B. T. Chen and M. Y. Chen, Applying particles swarm optimization for support vector machines on predicting company _nancial crisis, 2010 International Conference on Business and Economics Research, 1, (2011), 301-305
    Search in Google Scholar
  2. [2] C. Y. Chen and F. Ye, Particle Swarm Optimization Algorithm and Its Application to Clustering Analysis, Proceedings of the 2004 IEEE lnternational Conference on Networking, Sensing & Control, (2004), 789-794
    Search in Google Scholar
  3. [3] C. H. Chou, M. C. Su, and E. Lai, Symmetry as A New Measure for Cluster Validity, Proc. 2nd WSEAS Int. Conf. Sci. Comput. Soft Comput., (2002), 209-213
    Search in Google Scholar
  4. [4] L. Y. Chuang, Y. D. Lin, and C. H. Yang, An Improved Particle Swarm Op- timization for Data Clustering, Proceedings of the International MultiConference of Engineers and Computer Scientists, I, (2012), 440-445
    Search in Google Scholar
  5. [5] S. Das, A. Abraham, and A. Konar, Automatic kernel clustering with a Multi- Elitist Particle Swarm Optimization Algorithm, Pattern Recognition Letters, 29, (2008), 688-699
    Open DOISearch in Google Scholar
  6. [6] L. Dey and A. Mukhopadhyay, Microarray Gene Expression Data Clustering using PSO based K-means Algorithm, Proc. Int. Conf. Advanced Computing, Com- munication and Networks (ICACCN-2011), (2011), 587-591
    Search in Google Scholar
  7. [7] J. C. Dunn, Well Separated Clusters and Optimal Fuzzy Partitions, Journal of Cybernetica, 4, (1974), 95-104
    Open DOISearch in Google Scholar
  8. [8] R. C. Eberhart and J. Kennedy, A new optimizer using particle swarm theory, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, (1995), 39-43
    Search in Google Scholar
  9. [9] R. C. Eberhart and Y. Shi, Particle Swarm Optimization: Developments, Appli- cations and Resources, Proc. IEEE International Conference on Evolutionary Com- putation, 1, 81-86
    Search in Google Scholar
  10. [10] D. Enăchescu, Statistical Techniques of Data Mining (in Romanian), Editura Uni- versitatii din Bucuresti, Bucuresti, 2003
    Search in Google Scholar
  11. [11] M. G. Genton, Classes of Kernels for Machine Learning: A Statistics Perspective, Journal of Machine Learning Research, 2, (2001), 299-312
    Search in Google Scholar
  12. [12] N. I. Ghali, N. El-Dessouki, A. N. Mervat, and L. Bakrawi, Exponential Particle Swarm Optimization Approach for Improving Data Clustering, International Journal of Electrical and Electronics Engineering, 3, (2009), 208-212
    Search in Google Scholar
  13. [13] N. Ilc, Modied Dunns cluster validity index based on graph theory, Electrical Re- view, Poland, 2, (2012), 126-131
    Search in Google Scholar
  14. [14] A. K. Jain, M. N. Murty, and P. J. Flynn, Data Clustering: A Review, ACM Computing Reviews, (1999)
    Open DOISearch in Google Scholar
  15. [15] J. Kennedy and R. C. Eberhart, Particle swarm optimization, Proceedings of the IEEE International Conference on Neural Networks, IV, (1995), 1942-1948
    Search in Google Scholar
  16. [16] J. Kennedy and R. C. Eberhart, Swarm Intelligence, Academic Press, USA, 2001
    Search in Google Scholar
  17. [17] A. Khan, N. G. Bawane, and S. Bodkhe, An Analysis of Particle Swarm Opti- mization with Data Clustering-Technique for Optimization in Data Mining, Interna- tional Journal on Computer Science and Engineering, 2, (2010), 1363-1366
    Search in Google Scholar
  18. [18] F. Kovács, C. Legány, and A. Babos, Cluster Validity Measurement Techniques, Proceedings of the 5th WSEAS International Conference on Arti_cial Intelligence, Knowledge Engineering and Data Bases, (2006), 388-393
    Search in Google Scholar
  19. [19] K. Kryszczuk and P. Hurley, Estimation of the number of clusters using multiple clustering validity indices, MCS'10 Proceedings of the 9th international conference on Multiple Classi_er Systems, (2010), 114-123
    Open DOISearch in Google Scholar
  20. [20] M. A. Montes de Oca, Particle Swarm Optimization. Introduction, http://iridia.ulb.ac.be/_mmontes/slidesCIL/slides.pdf, last accessed February 2012, (2007)
    Search in Google Scholar
  21. [21] M. Neshat, S. F. Yazdi, D. Yazdani, and M. Sargolzaei, A New Cooperative Algorithm Based on PSO and K-Means for Data Clustering, Journal of Computer Science, 8, (2012), 188-194
    Open DOISearch in Google Scholar
  22. [22] M. Parimala, D. Lopez, and N.C. Senthilkumar, A Survey on Density Based Clustering Algorithms for Mining Large Spatial Databases, International Journal of Advanced Science and Technology, 31, (2011)
    Search in Google Scholar
  23. [23] P. Rai and S. Singh, A Survey of Clustering Techniques, International Journal of Computer Applications (0975 8887), 7, (2010)
    Open DOISearch in Google Scholar
  24. [24] S. C. Satapathy, G. Pradhan, S. Pattnaik, J. V. R. Murthy, and P. V. G. D. P. Reddy, Performance Comparisons of PSO based Clustering, InterJRI Computer Science and Networking, 1, (2009), 18-23
    Search in Google Scholar
  25. [25] J. Shawe-Taylor and N. Cristianini, Kernel Methods for Pattern Analysis, Cam- bridge University Press, New York, 2004
    Open DOISearch in Google Scholar
  26. [26] S. Theodoridis and K. Koutroumbas, Pattern Recognition 3rd Edition, Acca- demic Press, 2006
    Search in Google Scholar
DOI: https://doi.org/10.2478/awutm-2013-0007 | Journal eISSN: 1841-3307 | Journal ISSN: 1841-3293
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Language: English
Page range: 91 - 108
Published on: Aug 14, 2013
Published by: West University of Timisoara
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
clustering algorithm,
kernel function,
Particle Swarm Optimization,
discriminant function,
emergent behaviour
Related subjects:
Mathematics,
General mathematics

© 2013 Bianca Mogoş, Andrei-Horia Mogoş, published by West University of Timisoara
This work is licensed under the Creative Commons License.

Volume 51 (2013): Issue 1 (June 2013)
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