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A New Method for Generating Nonlinear Correction Models of Dynamic Objects 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

The purpose of nonlinear correction modelling of dynamic object is to use an approximated linear model of an object and determine corrections of this model in an appropriate way, taking into account the specificity of modelled nonlinearity. In this paper a new method for generating the coefficients of correction matrices is proposed. This method uses a mathematical formulas determined automatically by the Gene Expression Programming algorithm extended by semantic operator.

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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, Częstochowa University of Technology, Częstochowa, Poland

    Łukasz Bartczuk

  2. Moscow Institute of Physics and Technology, Moscow, Russia

    Alexander I. Galushkin

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  1. Łukasz Bartczuk
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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., Galushkin, A.I. (2016). A New Method for Generating Nonlinear Correction Models of Dynamic Objects 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_22

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