• Supreet Kaur

The world where we live is full of ambiguities. In earlier days, there was no mathematical concept to define vagueness. The laws of logic, the law of identity, the law of non-contradiction and the law of excluded middleware introduced and can be applied in any kind situation. In classical set theory, the membership of elements in a set is assessed in binary terms according to a bivalent condition — an element either belongs or does not belong to the set. By contrast, fuzzy set theory permits the gradual assessment of the membership of elements in a set; this is described with the aid of a membership function valued in the real unit interval [0, 1]. Fuzzy sets generalize classical sets, since the characteristic functions of classical sets are special cases of the membership functions of fuzzy sets, if the latter only take values 0 or 1.In fuzzy set theory, classical bivalent sets are usually called crisp sets. The fuzzy set theory can be used in a wide range of domains in which information is incomplete or imprecise. This paper presents an brief overview of fuzzy sets which cuts across some definitions, operations, properties, operators and extension principle on fuzzy sets.

Crisp sets, extension principle, fuzzy sets, membership functions, type-2 fuzzy sets

"An Overview of Fuzzy Sets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.404-410, July-2018, Available :http://www.jetir.org/papers/JETIR1807065.pdf

"An Overview of Fuzzy Sets", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp404-410, July-2018, Available at : http://www.jetir.org/papers/JETIR1807065.pdf