Fuzzy estimation for the difference between two means using different algorithms

New fuzzy algorithms for estimating the difference between two means of two independent random samples have been presented. Algorithms calculations have been done using different assumptions under condition the fuzziness of data which has been defined as Triangular Fuzzy Number because of its simplicity in calculations and its wide use in various applications. First, providing the estimation of the difference between two means by considering the two variances of each sample are known. Second, considering the two variances of the two samples are unknown but equal. Third, estimating the difference between two means by considering the two variances are unknown and unequal. Then, under the same assumptions of variances in the preceding three assumptions the difference between two means under condition crisp data based on different significance levels has been calculated. Finally, the advantages of using fuzzy algorithms have been presented.