Akademik Veri Yönetim Sistemi
The 2nd International Conference on Applied Mathematics, Modeling and Computer Simulation (AMMCS 2022), Wuhan, Çin, 13 - 14 Ağustos 2022, ss.1-30, (Tam Metin Bildiri)
A statistical technique called correlation analysis is used to determine the link between two variables and gauge how strongly two variables are linearly related. The degree of change in one variable as a result of the other's change is determined via correlation analysis. The correlation coefficient is one of the statistical ideas that are most relevant to this kind of investigation. The correlation coefficient, which is easily recognized by its symbol $r$ and typical value without units falling between 1 and -1, is the unit of measurement used to determine the intensity of the linear relationship between the variables included in correlation analysis. One of the best at representing completely ambiguous and uncertain information is the Fermatean fuzzy set. In this research, we present correlation coefficients and weighted correlation coefficient formulation to evaluate the relationship between two Fermatean fuzzy hypersoft sets, taking into account that the correlation coefficient plays a significant role in statistics and engineering disciplines. The Fermatean fuzzy hypersoft set is a parameterized family that deals with the sub-attributes of the parameters and is an appropriate extension of the Fermatean fuzzy soft set. It is also the generalization of the intuitionistic fuzzy hypersoft set and the Pythagorean fuzzy hypersoft set, which is used to accurately assess insufficiency, anxiety, and uncertainties in decision-making. The Fermatean fuzzy hypersoft set can accommodate more uncertainties compared to the intuitionistic fuzzy hypersoft set and Pythagorean fuzzy hypersoft set, and it is the most substantial methodology to describe fuzzy information in the decision-making process. One of the aims of this study is to give Fermatean fuzzy hypersoft sets and to examine their basic properties. The second objective of this study is to develop the notion and features of the correlation coefficient and the weighted correlation coefficient for the Fermatean fuzzy hypersoft set and to introduce the aggregation operators such as Fermatean fuzzy hypersoft weighted average and Fermatean fuzzy hypersoft weighted geometric operators under the Fermatean fuzzy hypersoft set scenario. A prioritization technique for order preference by similarity to the ideal solution (TOPSIS) under Fermatean fuzzy hypersoft set based on correlation coefficients and weighted correlation coefficients is presented. Through the developed methodology, a technique for solving the multi-attribute group decision-making problem is planned. In addition, examples of medical decision-making are presented for the importance and application of the developed methodology.