Affiliation:
1. Department of Mathematics, National Institute of Technology, Calicut 673 601, Kerala, India
2. Department of Mathematics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
Abstract
A spherical fuzzy soft set (SFSS) is a generalized soft set model, which is more sensible, practical, and exact. Being a very natural generalization, introducing uncertainty measures of SFSSs seems to be very important. In this paper, the concept of entropy, similarity, and distance measures are defined for the SFSSs and also, a characterization of spherical fuzzy soft entropy is proposed. Further, the relationship between entropy and similarity measures as well as entropy and distance measures are discussed in detail. As an application, an algorithm is proposed based on the improved technique for order preference by similarity to an ideal solution (TOPSIS) and the proposed entropy measure of SFSSs, to solve the multiple attribute group decision-making problems. Finally, an illustrative example is used to prove the effectiveness of the recommended algorithm.
Funder
University Grants Commission
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Civil and Structural Engineering,Computational Mechanics
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