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A Novel Modeling Methodology: Generalized Nets

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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 generalized net methodology was developed as a counterpart of Petri nets. The methodology allows to model different kinds of discrete dynamic systems. The basics of the theory of generalized nets is introduced and next the algorithm of generalized nets is described. Algebraic aspects of generalized nets as well as operator aspects of generalized nets are described. At the end, one possible application of generalized nets, namely for neural networks is shown. Here a neural network without any aggregation is considered.

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References

  1. Atanassov, K.: Generalized nets. World Scientific, Singapore, New Jersey, London (1991)

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  2. Atanassov, K.: Generalized Nets and Systems Theory, Prof. M. Drinov. Academic Publishing House, Sofia (1997)

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  3. Krawczak, M.: Multilayer Neural Systems and Generalized Net Models. Academic Press EXIT, Warsaw (2003)

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Author information

Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw School of Information Technology, Newelska 6, 01-447, Warsaw, Poland

    Maciej Krawczak

Authors
  1. Maciej Krawczak
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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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Krawczak, M. (2006). A Novel Modeling Methodology: Generalized Nets. 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_121

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  • DOI: https://doi.org/10.1007/11785231_121

  • 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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