Decision making using algebraic operations on soft effect matrix as new category of similarity measures and study their application in medical diagnosis problems

Abstract

 A new category of similarity measures is investigated in this work, we first introduce the concept of effect matrix $\stackrel{\wedge }{T}({\mathfrak{R}}_1\times {\mathfrak{R}}_2,p_n,q_m)$ of type 2-tuple and study some of their properties. Moreover, from the soft set we find the pictures of type regular and irregular using effect matrix $\stackrel{\wedge }{T}({\mathfrak{R}}_1\times {\mathfrak{R}}_2,p_n,q_m)$ of type 2-tuple. An effect matrix $\stackrel{\wedge }{T}({\mathfrak{R}}_1\times {\mathfrak{R}}_2,p_n,q_m)$ of type 2-tuple is better than effect matrix $\stackrel{\wedge }{E}(\mathfrak{R},p_n,q_m)$ of type 1-tuple, because we can deal with two different sets ${\mathfrak{R}}_1$ (a family of objectives) and ${\mathfrak{R}}_2$ (a family of parameters) in the same problem. This burden can be alleviated by application of type 2-tuple. Some applications of soft effect matrix of type 2-tuple $\stackrel{\wedge }{T}({\mathfrak{R}}_1\times {\mathfrak{R}}_2,p_n,q_m)$ in decision making problems are studied and explained. In this work we deal with pictures. Moreover, the similarity measure between two different soft sets under the same universal soft set $({\mathfrak{R}}_1\times {\mathfrak{R}}_2)$ can be studied and explained its applications in medical diagnosis problems.