@ARTICLE{Ganie_Abdul_Haseeb_A_2024,
 author={Ganie, Abdul Haseeb and Dutta, Debashis},
 volume={vol. 34},
 number={No 1},
 journal={Archives of Control Sciences},
 pages={63-82},
 howpublished={online},
 year={2024},
 publisher={Committee of Automatic Control and Robotics PAS},
 abstract={Spherical fuzzy sets are more powerful in modelling the uncertain situations than picture fuzzy sets, fermatean fuzzy sets, Pythagorean fuzzy sets, intuitionistic fuzzy sets, and fuzzy sets. In this paper, we first define the variance and covariance of spherical fuzzy sets. Then, using variance and covariance, we define the unique spherical fuzzy set correlation metric in line with the statistical coefficient of correlation. Two spherical fuzzy sets are correlated in both direction and strength using the provided measure of correlation. We discussed its many characteristics. We compared the measure of correlation with the current ones through linguistic variables. We established its validity by showing its application in bidirectional approximate reasoning. We also resolve a pattern identification issue in the spherical fuzzy environment using the provided correlation function, and we compare the results with several current measurements.},
 type={Article},
 title={A spherical fuzzy correlation coefficient based on statistical viewpoint with its applications in classification and bidirectional approximate reasoning},
 URL={http://ochroma.man.poznan.pl/Content/130770/art04_int.pdf},
 doi={10.24425/acs.2024.149652},
 keywords={correlation coefficient, fuzzy set, picture fuzzy set, spherical fuzzy sets, pattern recognition, bidirectional approximate reasoning},
}