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A Hypertube as a Possible Interpolation Region of a Neural Model

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Artificial Intelligence and Soft Computing – ICAISC 2006 (ICAISC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

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Abstract

The aim of this article is to present a method which can be applied to determine interpolation region of a multidimensional neural model. The method is based on the parametric curve modelling. The idea of it is to surround the parametric curve model with the hypertube covering most of the data points used in a neural model training. The practical application of the method will be shown via a system of an unemployment rate in Poland in years 1992-1999.

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Author information

Authors and Affiliations

  1. University of Szczecin, 64/66 Mickiewicza Street, 71-101, Poland

    Izabela Rejer & Marek Mikolajczyk

Authors
  1. Izabela Rejer
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  2. Marek Mikolajczyk
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Editor information

Editors and Affiliations

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

    Leszek Rutkowski

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

    Ryszard Tadeusiewicz

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

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Rejer, I., Mikolajczyk, M. (2006). A Hypertube as a Possible Interpolation Region of a Neural Model. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_14

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  • DOI: https://doi.org/10.1007/11785231_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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