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Let μ be a fuzzy set in a BCI-algebra X.
Fuzzy number: Let A be a fuzzy set in R (set of real numbers).
(mathbf{alpha -cut}): Let A be a fuzzy set in X and (alpha in (0,1]).
Let X be an arbitrary nonempty set, ∗ be a continuous t-norm,and M be a fuzzy set on X 2 × ( 0, ∞ ).
Due to some disturbances, the blood pressure measurement is an ambiguous process; thus, the given data should be a fuzzy set.
Let (X=Bbb{N}), define (aast b=ab) for all (a,bin [0,1]), let M be a fuzzy set on (X^{2}times[0,infty)) as follows: M x,y,t) = textstylebegin{cases} frac{x+t}{y+t}, & x leq y, frac{y+t}{x+t}, & y >x. end{cases} Then ((X,M,ast)) is a fuzzy metric space. [7].
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Let f : L E ∩ C E be a fuzzy set-value function.
Let X be a real vector space and let (f:Xrightarrowmathcal {F}_{KC}(Y)) be a fuzzy set-valued mapping.
The main objective of this paper is to further extend and establish some new Ulam type stability results of the quadratic functional equations mentioned above, in which the quadratic mapping is assumed to be a fuzzy set-valued mapping.
Example 4.2 Let f : R → R be the function defined in Example 4.1, and let F ˜ : R → F ( R ) be a fuzzy set-valued mapping defined as, for each x ∈ R, F ˜ ( x ) ( y ) = max { − 1 | f ( x ) | | y − f ( x ) | + 1, 0 }. for each y ∈ R if f ( x ) ≠ 0, and F ˜ ( x ) ( y ) = { 1 if y = 0, 0 if y ≠ 0. for each y ∈ R if f ( x ) = 0.
Fuzzy set theory is developed for handing uncertainty, imprecision and complexity in the real world; for example, we say "driving speed is high" wherein speed is a fuzzy variable and high is a fuzzy set, which uses the membership function to indicate the degree of a element belonging to the set (words in Italics to denote fuzzy variables or fuzzy sets).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com