Abstract: Soft set theory is a newly emerging mathematical tool to deal with uncertain problems. In this paper, we proposed the definition of T-product of intuitionistic fuzzy soft matrices with examples. Finally, We extend our approach in application of these matrices in decision making problem, by using medical diagnosis.

We present some connections between the max-min general fuzzy automaton theory and the hyper structure theory. First, we introduce a hyper BCK-algebra induced by a max-min general fuzzy automaton. Then, we study the properties of this hyper BCK-algebra. Particularly, some theorems and results for hyper BCK-algebra are proved. For example, it is shown that this structure consists of different ty...

This paper considers the main positions of one-sided and two-sided problems. For onesided problems only the method of solution “the distance to the ideal point” is discussed in the actual version. For two-sided problems a distinction is made between games with rational behaviour and games against nature. The main strategic principles are as follows: simple min-max principle, extended min-max pr...

In 2013 Ayman A. Hazaymeh in his PhD thesis introduced the concept of timefuzzy soft set as a generalization of fuzzy soft set. In this paper and as a generalization of neutrosophic soft set we introduce the concept of time-neutrosophic soft set and study some of its properties. We also, define its basic operations, complement, union intersection, ”AND” and ”OR” and study their properties. Also...

Most decision making methods used to evaluate a system or demonstrate the weak and strength points are based on fuzzy sets and evaluate the criteria with words that are modeled with fuzzy sets. The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods. For this reason, the decision making methods that consider the perceptions of decision...

By means of Dubois and Prade’s idea, we introduce the concept of rough fuzzy normal subgroups and investigate some related properties. Combining rough sets and soft sets, rough soft normal subgroups with respect to a normal subgroup of groups in Pawlak approximation spaces are introduced. Moreover, we investigate the relationships between lower and upper rough soft normal subgroups with respect...

Abstract This paper has represented a soft-set in the type-2 environment by its simplest form as an augmentation to theories. Furthermore, we have applied fuzzy soft set(T2FSS) using our most straightforward representation find solution of decision-making-problem (DMP) based-on T2FSS well weighted set (WT2FSS). We proposed two definitions, namely, Mid- $$\alpha $$ <mml:math xmlns:mml="http://ww...

The growth in amount of data available today has encouraged the development of effective data analysis methods to support human decision-making. Neuro-fuzzy computation is a soft computing hybridisation combining the learning capabilities of the neural networks with the linguistic representation of data provided by the fuzzy models. In this paper, a framework to build temporally local neuro-fuz...

Fault diagnosis is a complex and fuzzy cognitive process, and soft computing methods and technologies based on Neural Networks (NN) and Fuzzy Logic (FL), have shown great potential in the development of Decision Support Systems (DSS). Dealing with expert (human) knowledge consideration, Computer Aided Diagnosis (CAD) dilemma is one of the most interesting, but also one of the most difficult pro...

The following optimization problem is studied. There are several sets of integer positive numbers whose values are uncertain. The problem is to select one representative of each set such that the sum of the selected numbers is minimum. The uncertainty is modeled by discrete and interval scenarios, and the min–max and min–max (relative) regret approaches are used for making a selection decision....