interval-valued intuitionistic fuzzy sets (ivifss) are widely used to handle uncertainty and imprecision in decision making. however, in more complicated environment, it is difficult to express the uncertain information by an ivifs with considering the decision-making preference. hence, this paper proposes a group generalized interval-valued intuitionistic fuzzy soft set (g-givifss) which conta...

In this paper, we propose a faceted requirement classification scheme for analyzing heterogeneous requirements. The representation of vague requirements is based on Zadeh’s canonical form in test-score semantics and an extension of the notion of soft conditions. The trade-off among vague requirements is analyzed by identifying the relationship between requirements, which could be either conflic...

The soft set theory is a newly mathematical tool to deal with uncertain problems. However, the classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. In this paper, we introduce the average function and propose the interval-valued intuitionistic hesitant fuzzy soft sets (IVIHFSSs) which are a combination of the interval-valued intuitionistic hesitant fuzzy sets and...

Dynamic chemical reactions at the surface of liposomes are of fundamental interest to the understanding of physiological processes at biological membranes and can be exploited to prepare responsive soft materials. In this paper we describe a covalent yet reversible reaction between liposomes. To this end we explored the reversible thioester exchange reaction of membrane embedded amphiphilic thi...

One of the most important and challenging questions in the area of clustering is how to choose the best-fitting algorithm and parameterization to obtain an optiml clustering for the considered data. The clustering aggregation concept tries to bypass this problem by generating a set of separate, heterogeneous partitionings of the same data set, from which an aggregate clustering is derived. Up t...

A medical diagnosis is one the most efficient processes of determining a disease based on person’s symptoms and signs. In recent days, due to complexities same type diseases, it very difficult diagnose by using old methods techniques. this way, new can help lot in reaching an accurate conclusion, depending upon timing sequences history. The physician relies other clues like tests imaging tests....

in this paper, based in the l ukasiewicz logic, the definition offuzzifying soft neighborhood structure and fuzzifying soft continuity areintroduced. also, the fuzzifying soft proximity spaces which are ageneralizations of the classical soft proximity spaces are given. severaltheorems on classical soft proximities are special cases of the theorems weprove in this paper.

We consider scenarios where several agents must aggregate their preferences over a large set of candidates with a combinatorial structure. That is, each candidate is an element of the Cartesian product of the domains of some variables. We assume agents compactly express their preferences over the candidates via soft constraints. We consider a sequential procedure that chooses one candidate by a...

We consider a scenario where several agents express their preferences over a common set of variable assignments, by means of a soft constraint problem for each agent, and we propose a procedure to compute a variable assignment which satisfies the agents’ preferences at best. Such a procedure considers one variable at a time and, at each step, asks all agents to express its preferences over the ...