Issue:Modified and generalized correlation coefficient between intuitionistic fuzzy sets with applications

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Title of paper: Modified and generalized correlation coefficient between intuitionistic fuzzy sets with applications
Author(s):
Paul Augustine Ejegwa
Department of Mathematics/Statistics/Computer Science, University of Agriculture, P.M.B. 2373, Makurdi, Nigeria
ejegwa.augustineAt sign.pnguam.edu.ng
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 26 (2020), Number 1, pages 8–22
DOI: https://doi.org/10.7546/nifs.2020.26.1.8-22
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Abstract: Intuitionistic fuzzy set (IFS) is a very interesting soft computing technique use to tackle/handle imprecisions embedded in multi-criteria decision-making (MCDM) problems.

Correlation coefficient has proven to be an important measuring operator in an intuitionistic fuzzy setting with regard to its applications in solving MCDM problems. In this paper, Xu et al.’s method of correlation coefficient between IFSs is modified because it fails the axiomatic properties of correlation coefficient between IFSs, and hence generalized for a better output. That is, this paper is aimed at modifying and generalizing the triparametric correlation coefficient for IFSs proposed by Xu et al. with applications to some MCDM problems. Some numerical examples are supplied to authenticate the superiority of this new correlation coefficient for IFSs over some similar existing correlation coefficient measures. Subsequently, some MCDM problems such as medical diagnosis and pattern recognition problems represented in intuitionistic fuzzy pairs are determined with the aid of the novel correlation coefficient. An intuitionistic fuzzy clustering algorithm based on this novel correlation coefficient with applications could be an interesting research for future work.

Keywords: Fuzzy set, Intuitionistic fuzzy set, Correlation coefficient, Multi-criteria decision making.
AMS Classification: 03E72, 62H20, 62M10.
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