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Intuitionistic Fuzzy ANOVA and Its Application Using Different Techniques

  • D. KalpanapriyaEmail author
  • M. Mubashir Unnissa
Conference paper
Part of the Trends in Mathematics book series (TM)

Abstract

A fuzzification is the conversion of an exact quantity to uncertainty. A more generalized fuzzy set called intuitionistic fuzzy set is defuzzified to propose its application in career development to find the homogeneity among students and their career using analysis of variance (ANOVA). The proposed test procedure is well illustrated using a numerical example. The main purpose of this paper is to give a view of intuitionistic fuzzy set with the application of ANOVA technique to emphasize the efficiency in career development.

Keywords

Fuzzy set Intuitionistic fuzzy set Defuzzification ANOVA 

References

  1. 1.
    Q. Ansari, S. A. Siddiqui, J. A. Alvi :Mathematical techniques to convert intuitionistic fuzzy sets into fuzzy sets.Note on IFS 10,13–17(2004)Google Scholar
  2. 2.
    Alireza Jiryaei, Abbas Parchami and Mashaalla Mashinchi: One-way Anova and least squares method based on fuzzy random variables, Turkish Journal of Fuzzy Systems, 4, 18–33 (2013)Google Scholar
  3. 3.
    Atanassov.K.T :New operations defined over intuitionistic fuzzy sets, Fuzzy sets and Systems, 6,137–142.(1994)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Atanassov: K. Intuitionistic fuzzy sets . In Proceedings of the VII ITKR’s Session, Sofia (1983)Google Scholar
  5. 5.
    K.T. Atanassov: Intuitionistic fuzzy sets, Fuzzy Sets and Systems,20, 87–96(1986).MathSciNetCrossRefGoogle Scholar
  6. 6.
    J.L.Devore, Probability and Statistics for Engineers, Cengage, 2008Google Scholar
  7. 7.
    D. Kalpanapriya and P. Pandian: Statistical Hypotheses testing for imprecise data, Applied Mathematical Sciences, 6, 5285–5292 (2012)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Konishi,M., T. Okuda and K. Asai : Analysis of variance based on fuzzy interval data using moment correction method, International Journal of Innovative Computing, Information and Control, 2, 83–99 (2006)Google Scholar
  9. 9.
    Arefi, M., and S.M. Taheri :Testing fuzzy hypotheses using fuzzy data based on fuzzy test statistic, Journal of Uncertain Systems, Vol. 5, No.1, pp. 45–61 (2011)Google Scholar
  10. 10.
    Wu, H.C : Statistical confidence intervals for fuzzy data, Expert Systems with Applications, 36, 2670–267(2006)CrossRefGoogle Scholar
  11. 11.
    Zadeh, L.A: Probability measures of fuzzy events, Journal of Mathematical Analysis and Applications, 23, 421–427 (1968)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Paul Augustine Ejegwa: Mathematical techniques to transform intuitionistic fuzzy multisets to fuzzy sets. Journal of Information and Computing Science.2,169–172(2015)Google Scholar
  13. 13.
    Akbari, M.G., and A. Rezaei: Bootstrap statistical inference for the variance based on fuzzy data, Austrian Journal of Statistics, 38,121–130(2009)CrossRefGoogle Scholar
  14. 14.
    Nourbakhsh M, M. Mashinchbi and A. Parchami: Analysis of Variance based on fuzzy observations, International Journal of Systems Science, 44, 714–726 (2013).MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Mathematics, School of Advanced SciencesVIT UniversityVelloreIndia

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