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Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I pp 157–174Cite as

Weighted Fuzzy Genetic Programming Algorithm for Structure and Parameters Selection of Fuzzy Systems for Nonlinear Modelling

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 521))

Abstract

In this paper a weighted fuzzy genetic programming algorithm for selection of structure and parameters of fuzzy systems for nonlinear modelling is proposed. This method is based on fuzzy genetic programming and innovations in this method concern, among the others, using weights of fuzzy aggregation operators, using weights of fuzzy rules, using fitness function criteria designed for fuzzy genetic programming and using dynamic links between fuzzy rules and fuzzy rules base. The proposed method was tested with use of typical nonlinear modelling problems.

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Acknowledgment

The project was financed by the National Science Centre (Poland) on the basis of the decision number DEC-2012/05/B/ST7/02138.

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Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

    Krystian Łapa & Krzysztof Cpałka

Authors
  1. Krystian Łapa
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  2. Krzysztof Cpałka
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Corresponding author

Correspondence to Krystian Łapa .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Faculty of Computer Science and Management, Wrocław University of Technology Department of IT and Management, Wrocław, Poland

    Leszek Borzemski

  2. Department of Computer Science, Faculty of Computer Science and Management, Wrocław University of Technology Department of Computer Science, Wrocław, Poland

    Adam Grzech

  3. Department of Computer Science, Faculty of Computer Science and Management, Wrocław University of Technology Department of Computer Science, Wrocław, Poland

    Jerzy Świątek

  4. Department of Management Systems, Faculty of Computer Science and Management, Wrocław University of Technology, Wrocła Department of Management Systems, Wrocław, Poland

    Zofia Wilimowska

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Łapa, K., Cpałka, K. (2017). Weighted Fuzzy Genetic Programming Algorithm for Structure and Parameters Selection of Fuzzy Systems for Nonlinear Modelling. In: Borzemski, L., Grzech, A., Świątek, J., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part I. Advances in Intelligent Systems and Computing, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-319-46583-8_13

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  • DOI: https://doi.org/10.1007/978-3-319-46583-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46582-1

  • Online ISBN: 978-3-319-46583-8

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