Abstract
Contemporary research has refined systems with complex fuzzy sets in order to improve the design and model of real-life applications. Symmetry and antisymmetry are basic characteristics of binary relations used when modeling the decision maker’s preferences. A recent focus has been the analysis of a complex data set using the properties of fuzzy concept lattice and the complex soft set. We will introduce a new concept to represent the information which utilizes the time factor, called fuzzy parameterized complex multi-fuzzy soft expert set ( F P - CMFSES ), and investigate part of its fundamental properties. This F P - CMFSES model allows us to validate the information provided by an expert, at a given phase of time, using the properties of complex fuzzy sets. We then construct an algorithm based on this concept by converting it from the complex state to the real state. Eventually, we implement it to a decision-making problem to demonstrate the applicability of the suggested method. A comparison among F P - CMFSES and other existing methods is made to expose the dominance of the suggested method. Apart from that, we also propose the weighted fuzzy parameterized complex multi-fuzzy soft expert set and investigate its application to decision-making.
Highlights
Numerous categories of uncertainties occur in almost every domain of our daily life, which calls for useful mathematic tools for handling these kinds of uncertainties
We have used the FP-CMF SE S to determine the appropriate country from the three countries to travel in terms of the living cost and weather, where its amplitude terms represent the degrees of belongingness to the living cost and weather and its phase terms represent the degrees of belongingness to the phase of seasons
We have presented the idea of FP-CMF SE S by giving an important degree to each parameter in the complex multi-fuzzy soft expert set (CMFSES)’s domain
Summary
Numerous categories of uncertainties occur in almost every domain of our daily life, which calls for useful mathematic tools for handling these kinds of uncertainties. Al-Qudah and Hassan [24] presented the concept of complex multi-fuzzy soft sets in order to assimilate the advantages of CMFS along with sufficient parameterization tools For making these models better functional in improving decision-making results, Al-Qudah and Hassan [25] suggested the theory of the complex multi-fuzzy soft expert set (CMFSES) in order to allow the users to be familiar with all of the experts’ opinion in a single model, neglecting the need for any further cumbersome operations.
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