# fuzzy set

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## fuzzy set

[′fəz·ē ′set]
(mathematics)
An extension of the concept of a set, in which the characteristic function which determines membership of an object in the set is not limited to the two values 1 (for membership in the set) and 0 (for nonmembership), but can take on any value between 0 and 1 as well.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
References in periodicals archive ?
First, we propose a modified non-membership function to generate intuitionistic fuzzy set, which highlights the effect of uncertainty and makes good use of image information.
To approximate those uncertainties exists in the given linguistics words the fuzzy set theory is introduced by Zadeh [10].
Fuzzy set theory (Zadeh, 1965) is tool that can handle uncertainty and imprecision effortlessly.
Atanassov [1] extends the fuzzy set characterized by a membership function to the intuitionistic fuzzy set (IFS), which is characterized by a membership function, a non-membership function, and a hesitancy function.
An intuitionistic fuzzy set offers a better way to deal with uncertain multi-attribute problems (Mehlawat & Grover, 2018; Rodriguez, Ortega, & Concepcion, 2017; Ren, Xu, & Wang, 2017; Khemiri, Elbedouimaktouf, Grabot, & Zouari, 2017; Ye, 2017).
Fuzzy set theory in fuzzy decision making processes was first introduced by Bellman and Zadeh (1970).
In fuzzy set theory, the measurement of the degree of fuzziness in fuzzy sets and other extended higher order fuzzy sets is an important concept in dealing with real world problems.
The purpose of this paper is to present an uncertainty management model that applies fuzzy set theory to these indicators.
Fuzzy set theory, introduced by Zadeh [1], can be used to deal with these factors in the modelling of the systems.
At this time, the people should use hybrid intuitionistic fuzzy set to make a decision.
For a nonlinear engineering problem, fuzzy set theory is very helpful, and a tool that transforms this linguistic control strategy into a mathematical control method in modeling complex and vague systems.
put forth a novel concept of soft rough fuzzy sets by combining rough sets, soft sets, and fuzzy sets and we call it Feng-soft rough fuzzy set [38].

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