Skip to main content

Part of the book series: Studies in Computational Intelligence ((SCI,volume 34))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berkhin P (2002) Survey of clustering data mining techniques. Technical report, Accrue Software, San Jose, California

    Google Scholar 

  2. Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York, NY

    MATH  Google Scholar 

  3. Deneubourg JL, Goss S, Franks N, Sendova-Franks A, Detrain C, Chretien L (1991) The Dynamics of Collective Sorting: Robot-like Ants and Ant-like Robots. In: Proc. First International Conference on Simulation of Adaptive Behaviour: From Animals to Animats, pp. 356-363, MIT Press, Cambridge, MA

    Google Scholar 

  4. Handl J, Knowles J, Dorigo M (2003) Ant-based clustering: a comparative study of its relative performance with respect to k-means, average link and 1D-som. Technical Report TR/IRIDIA/2003-24. IRIDIA, Universite Libre de Bruxelles, Belgium

    Google Scholar 

  5. Handl J, Knowles J, Dorigo M (2003) On the performance of ant-based clustering. In: Proc. 3nd International Conference on Hybrid Intelligent Systems, pp. 204-213, IOS Press, Amsterdam, The Netherlands

    Google Scholar 

  6. Kanade PM, Hall LO (2003) Fuzzy Ants as a Clustering Concept. In: Proc. 22nd International Conference of the North American Fuzzy Information Processing Society, pp. 227-232, Chicago, Piscataway, NJ: IEEE Service Center

    Google Scholar 

  7. Kennedy J, Eberhart RC (1995) Particle Swarm Optimization. In: Proc. IEEE International Conference on Neural Networks, pp. 1942-1948, Perth, Australia, IEEE Service Center, Piscataway, NJ

    Chapter  Google Scholar 

  8. . Kennedy J, Eberhart RC, Shi Y (2001) Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco, ISBN: 1-55860-595-9

    Google Scholar 

  9. . Monmarche N, Slimane M, Venturini G (1999) AntClass: discovery of clusters in numeric data by an hybridization of an ant colony with the kmeans algorithm. Internal Report No. 213, E3i, Laboratoire d’Informatique, Universite de Tours

    Google Scholar 

  10. Morse DH (1970) Ecological aspects of some mixed-species foraging flocks of birds. Ecological Monographs: Vol. 40, No. 1, pp. 119-168

    Article  MathSciNet  Google Scholar 

  11. . Murphy PM, Aha DW (1994) UCI Repository of machine learning databases. [http://www.ics.uci.edu/∼mlearn/MLRepository.html], Irvine, CA: University of California, Department of Information and Computer Science

  12. . Omran M, Salman A, Engelbrecht AP (2002) Image Classification using Particle Swarm Optimization. In: Proc. 4th Asia-Pacific Conference on Simulated Evolution and Learning, pp. 370-374, Singapore

    Google Scholar 

  13. Reynolds CW (1987) Flocks, herds and schools: a disctributed behavioral model. Computer Graphics 21, pp. 25-33

    Article  Google Scholar 

  14. Shi YH, Eberhart RC (1998) A Modified Particle Swarm Optimizer. In: Proc. IEEE International Conference on Evolutionary Computation, pp. 69-73, IEEE Press, Piscataway, NJ

    Google Scholar 

  15. van der Merwe DW, Engelbrecht AP (2003) Data clustering using particle swarm optimization. In: Proceedings of the 2003 IEEE Congress on Evolutionary Computation, pp. 215-220, Piscataway, NJ: IEEE Service Center

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Veenhuis, C., Köppen, M. (2006). Data Swarm Clustering. In: Abraham, A., Grosan, C., Ramos, V. (eds) Swarm Intelligence in Data Mining. Studies in Computational Intelligence, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34956-3_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-34956-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34955-6

  • Online ISBN: 978-3-540-34956-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics