Decision making using new category of similarity measures and study their applications in medical diagnosis problems

Abstract

The aim of this paper is to propose a new category of similarity measures, we begin to introduce the concept of effect matrix $$\mathop T\limits^{ \wedge } (R_{1} \times R_{2} \times R_{3} ,p_{m} ,q_{n} ,f_{v} )$$ of type 3-tuple and study some of their properties. Moreover, from the soft set we find the pictures of type regular and irregular using effect matrix $$\mathop T\limits^{ \wedge } (R_{1} \times R_{2} \times R_{3} ,p_{m} ,q_{n} ,f_{v} )$$ of type 3-tuple are found. An effect matrix $$\mathop T\limits^{ \wedge } (R_{1} \times R_{2} \times R_{3} ,p_{m} ,q_{n} ,f_{v} )$$ of type 3-tuple is better than effect matrix $$\mathop T\limits^{ \wedge } (\Re_{1} \times \Re_{2} ,p_{n} ,q_{m} )$$ of type 2-tuple, because we can deal with three different sets $$R_{1}$$ (a family of objectives), $$R_{2}$$ (a family of parameters), $$R_{3}$$ (a family of second parameters) in the same problem. This burden can be alleviated by application of type 3-tuple. Some applications of soft effect matrix of type 3-tuple $$\mathop T\limits^{ \wedge } (R_{1} \times R_{2} \times R_{3} ,p_{m} ,q_{n} ,f_{v} )$$ 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 $$(R_{1} \times R_{2} \times R_{3} )$$ can be studied and explained its applications in medical diagnosis problems.