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Modified Kohonen Networks for Complex Cluster-Analysis Problems

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

The paper presents a modification of the self-organizing Kohonen networks for more efficient coping with complex, multidimensional cluster-analysis problems. The essence of modification consists in allowing the neuron chain – as the learning progresses – to disconnect and later to reconnect again. First, the operation of the modified approach has been illustrated by means of synthetic data set. Then, this technique has been tested with the use of a real-life, complex, multidimensional data set (Pen-Based Recognition of Handwritten Digits Database) available from the FTP server of the University of California at Irvine (ftp.ics.uci.edu).

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References

  1. Gorzałczany, M.B., Rudziński, F.: Application of Genetic Algorithms and Kohonen Networks to Cluster Analysis. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 556–561. Springer, Heidelberg (2004)

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  2. Machine Learning Database Repository, University of California at Irvine ftp.ics.uci.edu

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Kielce University of Technology, Al. 1000-lecia P.P. 7, 25-314, Kielce, Poland

    Marian B. Gorzałczany & Filip Rudziński

Authors
  1. Marian B. Gorzałczany
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  2. Filip Rudziński
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Gorzałczany, M.B., Rudziński, F. (2004). Modified Kohonen Networks for Complex Cluster-Analysis Problems. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_84

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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