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Published in: Artificial Intelligence Review 8/2021

17-02-2021

Algorithm for T-spherical fuzzy MADM based on associated immediate probability interactive geometric aggregation operators

Authors: Muhammad Munir, Tahir Mahmood, Azmat Hussain

Published in: Artificial Intelligence Review | Issue 8/2021

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Abstract

The purpose of writing this manuscript is to point out some limitations of existing associated immediate probability intuitionistic fuzzy geometric aggregation operators as these existing operators fail under some conditions such as the existing operators cannot handle the information given in Pythagorean fuzzy sets, picture fuzzy sets, spherical fuzzy sets, and T-spherical fuzzy sets and the existing aggregation operators also cannot aggregate the membership value when membership value of anyone intuitionistic fuzzy number become zero. To overcome these shortcomings associated immediate probability geometric aggregation operators have been developed for T-spherical fuzzy sets and associated immediate probability interactive geometric aggregation operators are proposed. Then a comparison between these operators is developed with the help of an example. The existing score function for T-spherical fuzzy sets does not involve abstinence so a new score function is developed which provides a better comparison between any two T-spherical fuzzy numbers. To demonstrate the presented algorithm, a decision-making process algorithm is presented with T-SFS features. The advantages of the proposed work are also discussed in which it is shown that under some conditions the proposed operators can be reduced to other tools of uncertainty. The comparison between existing and proposed work is also developed with the help of an example.

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Metadata
Title
Algorithm for T-spherical fuzzy MADM based on associated immediate probability interactive geometric aggregation operators
Authors
Muhammad Munir
Tahir Mahmood
Azmat Hussain
Publication date
17-02-2021
Publisher
Springer Netherlands
Published in
Artificial Intelligence Review / Issue 8/2021
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-021-09959-1

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