|
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.
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
Linking options:
https://www.mathnet.ru/eng/iipr263 https://www.mathnet.ru/eng/iipr/y2017/i4/p33
|
Statistics & downloads: |
Abstract page: | 48 | Full-text PDF : | 39 | References: | 1 |
|