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A method of building empirical models of the polynomial type for the case when the input factors are fuzzy variables with known Gaussian-type membership functions has been developed. It has been shown, that in such conditions the output model index is also a fuzzy value; the corresponding membership function, being the basis for the formation of the identi cation task, has been acquired.

MODELING OF TECHNOLOGICAL OBJECTS ON THE BASIS OF EXPERIMENTAL DATA IN CONDITIONS OF UNCERTAINTY