To overcome these drawbacks we apply

fuzzy set theory to multiple parameter decision making.

2014) Hamming distance method with subjective and objective weights along with

fuzzy set theory 32.

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 closed unit interval [0, 1].

On the capability of

Fuzzy Set Theory to represent concepts.

Fuzzy logic is derived from

fuzzy set theory and deals with a set of objects characterized by a membership function that assigns a grade of membership ranging between zero (no membership) and one (full membership) to each object (Shaheen et al, 2007).

The

fuzzy set theory is a powerful mathematical tool that uses linguistic terms to model the uncertainty resulted from the complexity of systems or sub-systems.

Fuzzy set theory, developed by Zadeh [1], has capability to describe the uncertain situations, containing ambiguity and vagueness.

For over fifty years,

fuzzy set theory has proven a useful an extension of the mathematical concept of a set.

As a result, instead of the exclusive use of crisp numbers, the

fuzzy set theory allows the use of other forms of numbers, such as triangular, trapezoidal, and bell-shaped numbers.

Intuitionistic

fuzzy set theory has emerged as a tool for its characterization.

He begins by setting out theoretical and logical aspects of classical, two-valued semantic web languages, then generalizes the languages to cope with

fuzzy set theory and fuzzy logic.

Fuzzy set theory and its applications, Kluwer Academic Publishers, ISBN 0-7293-7435-5, USA