Issue:An improved correlation coefficient between intuitionistic fuzzy sets and its applications to real-life decision-making problems

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Title of paper: An improved correlation coefficient between intuitionistic fuzzy sets and its applications to real-life decision-making problems
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 2, pages 1–14
DOI: https://doi.org/10.7546/nifs.2020.26.2.1-14
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Abstract: Correlation coefficient between intuitionistic fuzzy sets (CCIFSs) is a vital research area in intuitionistic fuzzy set theory and has great practical application in a variety of areas. Many methods of computing CCIFSs have been studied hitherto. Due to the weakness in some existing methods of computing CCIFSs, an advanced CCIFSs technique is proposed in this paper which has some advantages over the similar existing methods. This new CCIFSs technique is an improved version of some CCIFSs techniques. A set of numerical illustrations are given to determine the effectiveness of the introduced CCIFSs method over the similar existing ones. Furthermore, we apply the new technique of computing CCIFSs to solve real-life decisionmaking (RLDM) problems of personnel appointment exercise and career determination problem represented in intuitionistic fuzzy values. This proposed measuring tool could be exploited in other multi-criteria decision-making problems via cluster algorithm approach.
Keywords: Intuitionistic fuzzy set, Correlation coefficient measure, Real-life decision-making.
AMS Classification: 03E72, 62H20, 62M10.
References:
  1. Atanassov, K. T. (1986). Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20 (1), 87–96.
  2. Atanassov, K. T. (1994). New operations defined on intuitionistic fuzzy sets, Fuzzy Sets and Systems, 61, 137–142.
  3. Atanassov, K. T. (1999). Intuitionistic Fuzzy Sets: Theory and Applications. Physica-Verlag, Heidelberg.
  4. Atanassov, K. T. (2012). On Intuitionistic Fuzzy Sets Theory. Springer, Berlin.
  5. Chiang, D. A., & Lin, N.P. (1999). Correlation of fuzzy sets, Fuzzy Sets and Systems, 102 (2), 221–226.
  6. De, S. K., Biswas, R., & Roy, A. R. (2001). An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets and Systems, 117 (2), 209–213.
  7. Dumitrescu, D. (1977). A definition of an informational energy in fuzzy set theory, Studia University Babes-Bolyai Mathematics, 22, 57–59.
  8. Dumitrescu, D. (1978). Fuzzy correlation, Studia University Babes-Bolyai Mathematics, 23, 41–44.
  9. Ejegwa, P. A. (2015). Intuitionistic fuzzy sets approach in appointment of positions in an organization via max-min-max rule, Global Journal Science Frontier Research: Mathematics and Decision Science, 15 (6), 1–6.
  10. Ejegwa, P. A. (2020). Modified and generalized correlation coefficient between intuitionistic fuzzy sets with applications, Notes on Intuitionistic Fuzzy Sets, 26 (1), 8–22.
  11. Ejegwa, P. A., & Adamu, I. M. (2019). Distances between intuitionistic fuzzy sets of second type with application to diagnostic medicine, Notes on Intuitionistic Fuzzy Sets, 25 (3), 53–70.
  12. Ejegwa, P. A., Akubo, A. J., & Joshua, O. M. (2014). Intuitionistic fuzzy set and its application in career determination via normalized Euclidean distance method, European Scientific Journal, 10 (15), 529–536.
  13. Ejegwa, P. A., & Modom, E. S. (2015). Diagnosis of viral hepatitis using new distance measure of intuitionistic fuzzy sets, International Journal of Fuzzy Mathematical Archive, 8 (1), 1–7.
  14. Ejegwa, P. A., & Onasanya, B. O. (2019). Improved intuitionistic fuzzy composite relation and its application to medical diagnostic process, Notes on Intuitionistic Fuzzy Sets, 25 (1), 43–58.
  15. Ejegwa, P. A., & Onyeke, I. C. (2019). An object oriented approach to the application of intuitionistic fuzzy sets in competency based test evaluation, Annals of Communications in Mathematics, 1 (1), 38–47.
  16. Garg, H. (2016). A novel correlation coefficients between Pythagorean fuzzy sets and its applications to decision making processes, International Journal of Intelligent and Systems, 31 (12), 1234–1252.
  17. Gerstenkorn, T., & Manko, J. (1991). Correlation of intuitionistic fuzzy sets, Fuzzy Sets and Systems, 44 (1), 39–43.
  18. Hong, D. H., & Hwang, S. Y. (1995). Correlation of intuitionistic fuzzy sets in probability spaces, Fuzzy Sets and Systems, 75, 77–81.
  19. Hung, W. L. (2001). Using statistical viewpoint in developing correlation of intuitionistic fuzzy sets, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9 (4), 509–516.
  20. Hung, W. L., & Wu, J. W. (2002). Correlation of intuitionistic fuzzy sets by centroid method, Information Sciences, 144 (1), 219–225.
  21. Iqbal, M. N., & Rizwan, U. (2019). Some applications of intuitionistic fuzzy sets using new similarity measure, Journal of Ambient Intelligent and Humanized Computing, https: //doi.org/10.1007/s12652-019-01516-7.
  22. Kapes, J. T., Mastie, M. M., & Whitfield, E. A. (1994). A Counsellor’s Guide to Career Assessment Instruments, Alexandria, VA: National Career Development Association.
  23. Liu, B., Shen, Y., Mu, L., Chen, X., & Chen, L. (2016). A new correlation measure of the intuitionistic fuzzy sets, Journal of Intelligent and Fuzzy Systems, 30 (2), 1019–1028.
  24. Mitchell, H. B. (2004). A correlation coefficient for intuitionistic fuzzy sets, International Journal of Intelligent and Systems, 19 (5), 483–490.
  25. Szmidt, E., & Kacprzyk, J. (2001). Intuitionistic fuzzy sets in some medical applications, Notes on Intuitionistic Fuzzy Sets, 7 (4),58–64.
  26. Szmidt, E., & Kacprzyk, J. (2004). Medical diagnostic reasoning using a similarity measure for intuitionistic fuzzy sets, Notes on Intuitionistic Fuzzy Sets, 10 (4), 61–69.
  27. Szmidt, E., & Kacprzyk, J. (2010). Correlation of intuitionistic fuzzy sets, Lecture Notes on Computing Science, 6178, 169–177.
  28. Thao, N. X. (2018). A new correlation coefficient of the intuitionistic fuzzy sets and its application, Journal of Intelligent and Fuzzy Systems, 35 (2), 1959–1968.
  29. Thao, N. X., Ali, M., & Smarandache, F. (2019). An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis, Journal of Intelligent and Fuzzy Systems, 36 (1), 189–198.
  30. Todorova, L., Atanassov, K. T., Hadjitodorov, S., & Vassilev, P. (2007). On an intuitionistic fuzzy approach for decision-making in medicine (Part 1), International Electronic Journal of Bioautomation, 6, 92–101.
  31. Todorova, L., Atanassov, K. T., Hadjitodorov, S., & Vassilev, P. (2007). On an intuitionistic fuzzy approach for decision-making in medicine (Part 2), International Electronic Journal of Bioautomation, 7, 64–69.
  32. Xu, Z. (2006). On correlation measures of intuitionistic fuzzy sets, Lecture Notes on Computing Science, 4224, 16–24.
  33. Xu, S., Chen, J., & Wu, J. J. (2008). Cluster algorithm for intuitionistic fuzzy sets, Information Sciences, 178, 3775–3790.
  34. Zadeh, L. A. (1965). Fuzzy sets, Information and Control, 8, 338–353.
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