Fuzzy number approximation by trapezoidal fuzzy numbers which preserves the expected interval is discussed. New operators that fulfill additional requirements for the core and support of the fuzzy number are suggested. These supplementary conditions guarantee the proper interpretation of the solution even for very skew original fuzzy numbers.

In this article, we continue the development of the theory of fuzzy sets [23], started with [14] with the future aim to provide the formalization of fuzzy numbers [8] in terms reflecting the current state of the Mizar Mathematical Library. Note that in order to have more usable approach in [14], we revised that article as well; some of the ideas were described in [12]. As we can actually unders...

This study has developed a production inventory model where the cycle timeis fuzzy, the existence of defective products is assumed in each batch andproduct screening is performed both in-production and after-production.Triangular fuzzy numbers serve to model uncertainties in the cycle time, anda fuzzified total inventory profit function is created by thedefuzzifica...

Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations. Vector form of fuzzy c-means (VFCM), proposed in this paper, simplifies the FCM clustering method applying to non-crisp (symbolic interval and fuzzy) numbers. ...

There have been many increasing interests in fuzzy theory in the recent years, yet there are a lot of issues to be resolved, mainly on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. This study focuses on the development of triangular fuzzy numbers, the revising of triangular fuzzy numbers, and the constructing of a HCFN (half-...

Problem statement: The precision and reliability of the effort estimation is very important for the competitiveness of software companies. The uncertainty at the input level of the Constructive Cost Model (COCOMO) yields uncertainty at the output, which leads to gross estimation error in the effort estimation. Fuzzy logic-based cost estimation models are more appropriate when vague and imprecis...

the sst decomposition method for solving system of linear equations make it possible to obtain the values of roots of the system with the specified accuracy as the limit of the sequence of some vectors. in this topic we are going to consider vectors as fuzzy vectors. we have considered a numerical example and tried to find out solution vector x in fuzzified form using method of sst decomposition.

Linear programming (LP) is the most widely used optimization technique for solving real-life problems because of its simplicity and efficiency. Although LP models require well-suited information and precise data, managers and decision makers dealing with optimization problems often have a lack of information on the exact values of some parameters used in their models. Fuzzy sets provide a power...

This paper deals with derivation of analytical structures of fuzzy PI controllers consisting of N ≥ 3 number of triangular input fuzzy sets and 2N − 1 number of trapezoidal output fuzzy sets on the universe of discourse of input and output variables, respectively, linear control rules, different T-norms, different T-conorms, different inference methods, and center of area defuzzification method...