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Application of Models of Relational Fuzzy Cognitive Maps for Prediction of Work of Complex Systems

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Artificial Intelligence and Soft Computing (ICAISC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8467))

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Abstract

The paper presents certain aspects of application of model of the Relational Fuzzy Cognitive Map (RFCM) for advanced analysis of activity of complex dynamic systems. Intelligent models, including various types of cognitive maps, are commonly used to study the effect of the selected parameter on the others or to classification of objects described by many parameters. RFCM model characteristics, in addition to the above uses, allows to use it also for modeling the work of systems with the internal dynamics. It follows that such a model can be used to predict the state of the system in the future steps of a discrete time. In the paper, selected results of testing just such a use of the RFCM model are described.

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Authors and Affiliations

  1. Kielce University of Technology, al. Tysiaclecia P. P. 7, 25-314, Kielce, Poland

    Grzegorz Słoń

Authors
  1. Grzegorz Słoń
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Computer Science Division, Department of Electrical Engineering and Computer Sciences, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Słoń, G. (2014). Application of Models of Relational Fuzzy Cognitive Maps for Prediction of Work of Complex Systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8467. Springer, Cham. https://doi.org/10.1007/978-3-319-07173-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-07173-2_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07172-5

  • Online ISBN: 978-3-319-07173-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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