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Artificial Intelligence and Decision Making
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Artificial Intelligence and Decision Making, 2017, Issue 4, Pages 33–39 (Mi iipr263)  

Reasoning modelling methods

Method of fuzzy inference for one class of MISO-structure systems with fuzzy inputs

V. G. Sinuk, M. V. Panchenko

Belgorod Shukhov State Technological University
Abstract: In fuzzy modeling, the inputs of the simulated systems can receive both crisp values and fuzzy. Computational complexity of fuzzy inference with fuzzy inputs corresponds to an exponential. This paper describes a new method of inference, based on the theorem of decomposition of a multidimensional fuzzy implication and a fuzzy truth value. This method is considered for fuzzy inputs and has a polynomial complexity, which makes it possible to use it for modeling large-dimensional MISO-structure systems.
Keywords: logical type of inference, decomposition theorem, fuzzy truth value.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. G. Sinuk, M. V. Panchenko, “Method of fuzzy inference for one class of MISO-structure systems with fuzzy inputs”, Artificial Intelligence and Decision Making, 2017, no. 4, 33–39
Citation in format AMSBIB
\Bibitem{SinPan17}
\by V.~G.~Sinuk, M.~V.~Panchenko
\paper Method of fuzzy inference for one class of MISO-structure systems with fuzzy inputs
\jour Artificial Intelligence and Decision Making
\yr 2017
\issue 4
\pages 33--39
\mathnet{http://mi.mathnet.ru/iipr263}
\elib{https://elibrary.ru/item.asp?id=30771441}
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  • https://www.mathnet.ru/eng/iipr/y2017/i4/p33
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