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A New Method for Generating of Fuzzy Rules for the Nonlinear Modelling Based on Semantic Genetic Programming

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Artificial Intelligence and Soft Computing (ICAISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9693))

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Abstract

In this paper we propose a new approach for nonlinear modelling. It uses capabilities of the Takagi-Sugeno neuro-fuzzy systems and population based algorithms. The aim of our method is to ensure that created model achieves appropriate accuracy and is as compact as possible. In order to obtain this aim we incorporate semantic information about created fuzzy rules into process of evolution. Our method was tested with the use of well-known benchmarks from the literature.

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Acknowledgment

The project was financed by the National Science Center 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, Czȩstochowa University of Technology, Czȩstochowa, Poland

    Łukasz Bartczuk & Krystian Łapa

  2. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Petia Koprinkova-Hristova

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  1. Łukasz Bartczuk
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  2. Krystian Łapa
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  3. Petia Koprinkova-Hristova
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Correspondence to Łukasz Bartczuk .

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Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Bartczuk, Ł., Łapa, K., Koprinkova-Hristova, P. (2016). A New Method for Generating of Fuzzy Rules for the Nonlinear Modelling Based on Semantic Genetic Programming. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_23

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