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Foundations of Computational, Intelligence Volume 1 pp 363–379Cite as

Dynamic Self-Organising Maps: Theory, Methods and Applications

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 201))

Summary

In an effort to counter the restrictions enforced by the fixed map size and aspect ratio of a Kohonen Self-Organising Map, many variants to the method have been proposed. As a recent development, the Dynamic Self- Organising Map, also known as the Growing Self-Organising Map (GSOM), provides a balanced performance in topology preservation, data visualisation and computational speed. In this book chapter, a comprehensive description and theory of GSOM is provided, which also includes recent theoretical developments. Methods of clustering and identifying clusters using GSOM are also introduced here together with their related applications and results.

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Author information

Authors and Affiliations

  1. Biomechanical Engineering Research Group Department of Mechanical Engineering, Melbourne School of Engineering,  

    Isaam Saeed

  2. No Affiliations,  

    Arthur L. Hsu & Saman K. Halgamuge

Authors
  1. Arthur L. Hsu
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  2. Isaam Saeed
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  3. Saman K. Halgamuge
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Editor information

Editors and Affiliations

  1. College of Business Administration, Quantitative and Information System Department, Kuwait University, P.O. Box 5486, 13055, Safat, Kuwait

    Aboul-Ella Hassanien

  2. Center of Excellence for Quantifiable, Quality of Service, Norwegian University of Science & Technology, O.S. Bragstads plass 2E, 7491, Trondheim, Norway

    Ajith Abraham

  3. Department of Computer and Telecommunications Engineering, University ofWestern Macedonia, Agios Dimitrios Park, 50 100, Kozani, Greece

    Athanasios V. Vasilakos

  4. Dept. Electrical and Computer Engineering, University of Alberta, T6J 2V4, Edmonton,Alberta, Canada

    Witold Pedrycz

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© 2009 Springer-Verlag Berlin Heidelberg

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Hsu, A.L., Saeed, I., Halgamuge, S.K. (2009). Dynamic Self-Organising Maps: Theory, Methods and Applications. In: Hassanien, AE., Abraham, A., Vasilakos, A.V., Pedrycz, W. (eds) Foundations of Computational, Intelligence Volume 1. Studies in Computational Intelligence, vol 201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01082-8_14

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  • DOI: https://doi.org/10.1007/978-3-642-01082-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01081-1

  • Online ISBN: 978-3-642-01082-8

  • eBook Packages: EngineeringEngineering (R0)

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