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Abstract

In the present communication, we introduce the concept of Type-I generalized spherical interval valued fuzzy soft set and define some operations. It is a generalization of the interval valued fuzzy soft set and the spherical fuzzy soft set. The spherical interval valued fuzzy soft set theory satisfies the condition that the sum of its degrees of positive, neutral, and negative membership does not exceed unity and that these parameters are assigned independently. We also propose an algorithm to solve the decision making problem based on a Type-I generalized soft set model. We introduce a similarity measure based on the Type-I generalized soft set model for two Type-I generalized spherical interval valued fuzzy soft sets and discuss its application in a medical diagnosis problem. Illustrative examples are mentioned to show that they can be successfully used to solve problems with uncertainties.

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