Someone asks, why we don’t use the statistic instead of fuzzy logic? More detailed difference between the concepts led us use one instead of the other. That is, the difference between the degree of membership in the set (of some member), and a probability of being in that set.

The point of difference is, the probability involves a crisp set theory (probability of it belongs to class or not), and don’t allow for an element to be a partial member in a class (or a set, as in fuzzy logic1).

Probability is an indicator of frequency or likelihood that an element is in a class, while fuzzy set theory deals with the similarity of an element to a class [3] that is between elements in a class.

Anyone who doesn’t know and haven t study fuzzy logic and fuzzy sets think ,that fuzziness is just a clever disguise for probability, which is never true for more information see [1].

Although fuzzy logic is known latterly ,it has been communicated with many other sciences for its benefits in practical applications(applicable branches).Since 1991, fuzzy logic is used in technology as an industrial tool in reference[5]to be fuzzy control, but the theoretical side stay requisite .

Probability theory and fuzzy set theory have been communicated since they were depend on same range to be in closed interval]1,0[ ,also membership function(MF) that characterize the fuzzy set depend on some parameters(time_ verify parameters)and its values chosen from parameter space(real number).While probability distribution also depend on parameters describe the distribution and determine its values and shape ,which chosen from parameter space, many ways used to locate these parameter values.