A Perspective on Differences Between Atanassov’s Intuitionistic Fuzzy Sets and Interval-Valued Fuzzy Sets

  • Chapter
  • First Online:
Fuzzy Sets, Rough Sets, Multisets and Clustering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 671))

  • 1008 Accesses

Abstract

In the paper we show our perspective on some differences between Atanassov’s intuitionistic fuzzy sets (A-IFSs, for short) and Interval-valued fuzzy sets (IVFSs, for short). First, we present some standard operators and extensions for the A-IFSs which have no counterparts for IVFSs. Next, we show on an example a practical application based on one of such operators. We also revisit, and further analyze, the concepts of two possible representations of A-IFSs: the two term one, in which the degrees of membership and non-membership are only involved, and the three term one, in which in addition to the above degrees of membership and non-membership the so called hesitation margin is explicitly accounted for. Though both representations are mathematically correct and may be considered equivalent, the second one involves explicitly an additional, conceptually different information than the degree of membership and non-membership only even if it directly results from these two degrees. We then show on some examples of decision making type problems its intuitive appeal and usefulness for reflecting more sophisticated intentions and preferences of the user which cannot be fully reflected via their counterpart IVFSs based models. Finally, we recall different measures that are important from the point of view of applications. We consider the measures for both types representations of the A-IFSs pointing out some further differences in comparison to the case of the IVFSs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Atanassov K.T. (1983) Intuitionistic Fuzzy Sets. VII ITKR Session. Sofia (Deposed in Centr. Sci.-Techn. Library of Bulg. Acad. of Sci., 1697/84) (in Bulgarian).

    Google Scholar 

  2. Atanassov K.T. (1986) Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 20, 87–96.

    Article  MathSciNet  MATH  Google Scholar 

  3. Atanassov K. T. (1989) More on intuitionistic fuzzy sets. Fuzzy Sets and Systems, 33(1), 37–46.

    Article  MathSciNet  MATH  Google Scholar 

  4. Atanassov K.T. (1991) Temporal intuitionistic fuzzy sets. Comptes Rendus de l’Academie Bulgare des Sciences, Tome 44, No. 7, 5–7.

    Google Scholar 

  5. Atanassov K.T. (1999) Intuitionistic Fuzzy Sets: Theory and Applications. Springer-Verlag.

    Google Scholar 

  6. Atanassov K.T. (2006) Intuitionistic fuzzy sets and interval valued fuzzy sets. First Int. Workshop on IFSs, GNs, KE, London, 6–7 Sept. 2006, 1–7.

    Google Scholar 

  7. Atanassov K.T. (2012) On Intuitionistic Fuzzy Sets Theory. Springer-Verlag.

    Google Scholar 

  8. Atanassov K.T. and Gargov G. (1989) Interval Valued Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 31, 343–349.

    Article  MathSciNet  MATH  Google Scholar 

  9. Atanassov K., Tasseva V, Szmidt E. and Kacprzyk J. (2005): On the geometrical interpretations of the intuitionistic fuzzy sets. In: Issues in the Representation and Processing of Uncertain and Imprecise Information. Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets, and Related Topics. (Eds. Atanassov K., Kacprzyk J., Krawczak M., Szmidt E.), EXIT, Warsaw, 11–24.

    Google Scholar 

  10. Atanassova V. (2004) Strategies for Decision Making in the Conditions of Intuitionistic Fuzziness. Int. Conf. 8th Fuzzy Days, Dortmund, Germany, 263–269.

    Google Scholar 

  11. Bujnowski P., Szmidt E., Kacprzyk J. (2014): Intuitionistic Fuzzy Decision Trees - a new Approach. In: Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L., urada J. (Eds.): Artificial Intelligence and Soft Computing, Part I. Springer, Switzerland, 181–192.

    Google Scholar 

  12. Bustince H., Mohedano V., Barrenechea E., and Pagola M. (2005): Image thresholding using intuitionistic fuzzy sets. In: Issues in the Representation and Processing of Uncertain and Imprecise Information. Fuzzy Sets, Intuitionistic Fuzzy Sets, Generalized Nets, and Related Topics. (Eds. Atanassov K., Kacprzyk J., Krawczak M., Szmidt E.), EXIT, Warsaw.

    Google Scholar 

  13. Bustince H., Mohedano V., Barrenechea E., and Pagola M. (2006): An algorithm for calculating the threshold of an image representing uncertainty through A-IFSs. IPMU’2006, 2383–2390.

    Google Scholar 

  14. Bustince H., Barrenechea E., Pagola M., Fernandez J., Xu Z., Bedregal B., Montero J., Hagras H., Herrera F., and De Baets B., A Historical Account of Types of Fuzzy Sets and Their Relationships. IEEE Transactions on Fuzzy Systems, 24 (1), 2016, 179–194.

    Article  Google Scholar 

  15. Deng-Feng Li (2005): Multiattribute decision making models and methods using intuitionistic fuzzy sets. Journal of Computer and System Sciences, 70, 73–85.

    Article  MathSciNet  MATH  Google Scholar 

  16. Dubois D., Prade H.(2008): An introduction to bipolar representations of information and preference. Int. J. Intell. Syst. 23(8), 866–877.

    Article  MATH  Google Scholar 

  17. Feys R. Modal logic. Foundation Universitaire de Belgique, Paris 1965.

    MATH  Google Scholar 

  18. Grabisch M., Greco S., Pirlot M. (2008): Bipolar and bivariate models in multicriteria decision analysis: Descriptive and constructive approaches. International Journal of Intelligent Systems, 23 (9), 930–969.

    Article  MATH  Google Scholar 

  19. Kuratowski K. (1966) Topology, Vol. 1, New York, Acad. Press.

    MATH  Google Scholar 

  20. Montero J., Gmez D., Bustince Sola H. (2007): On the relevance of some families of fuzzy sets. Fuzzy Sets and Systems 158(22), 2429–2442.

    Article  MathSciNet  MATH  Google Scholar 

  21. Narukawa Y. and Torra V. (2006): Non-monotonic fuzzy measure and intuitionistic fuzzy set. MDAI 2006, LNAI 3885, 150–160, Springer-Verlag.

    Google Scholar 

  22. Roeva O. and Michalikova A. (2013) Generalized net model of intuitionistic fuzzy logic control of genetic algorithm parameters. In: Notes on Intuitionistic Fuzzy Sets. Academic Publishing House, Sofia, Bulgaria. Vol. 19, No. 2, 71–76. ISSN 1310-4926.

    Google Scholar 

  23. Szmidt E. (2014): Distances and Similarities in Intuitionistic Fuzzy Sets. Springer.

    Google Scholar 

  24. Szmidt E. and Baldwin J. (2003) New similarity measure for intuitionistic fuzzy set theory and mass assignment theory.

    Google Scholar 

  25. Szmidt E. and Baldwin J. (2004) Entropy for intuitionistic fuzzy set theory and mass assignment theory. Notes on IFSs, 10 (3), 15–28.

    Google Scholar 

  26. Szmidt E. and Baldwin J. (2006): Intuitionistic Fuzzy Set Functions, Mass Assignment Theory, Possibility Theory and Histograms. 2006 IEEE World Congress on Computational Intelligence, 237–243.

    Google Scholar 

  27. Szmidt E. and Kacprzyk J. (1997): On measuring distances between intuitionistic fuzzy sets. Notes on IFS, 3(4), 1–13.

    MathSciNet  MATH  Google Scholar 

  28. Szmidt E. and Kacprzyk J. (1999): Probability of Intuitionistic Fuzzy Events and their Applications in Decision Making. EUSFLAT-ESTYLF, Palma de Mallorca, 457–460.

    Google Scholar 

  29. Szmidt E. and Kacprzyk J. (1999b): A Concept of a Probability of an Intuitionistic Fuzzy Event. FUZZ-IEEE’99, Seoul, Korea, III 1346–1349.

    Google Scholar 

  30. Szmidt E., Kacprzyk J. (2000): Distances between intuitionistic fuzzy sets. Fuzzy Sets and Systems, 114 (3), 505–518.

    Article  MathSciNet  MATH  Google Scholar 

  31. Szmidt E., Kacprzyk J. (2001): Entropy for intuitionistic fuzzy sets. Fuzzy Sets and Systems, 118, Elsevier, 467–477.

    Google Scholar 

  32. Szmidt E., Kacprzyk J. (2006): Distances Between Intuitionistic Fuzzy Sets: Straightforward Approaches may not work. 3rd International IEEE Conference Intelligent Systems IEEE IS’06, London, 716–721.

    Google Scholar 

  33. Szmidt E. and Kacprzyk J. (2007): Some problems with entropy measures for the Atanassov intuitionistic fuzzy sets. Applications of Fuzzy Sets Theory. LNAI 4578, Springer-Verlag, 291–297

    Google Scholar 

  34. Szmidt E. and Kacprzyk J. (2007a): A New Similarity Measure for Intuitionistic Fuzzy Sets: Straightforward Approaches may not work. 2007 IEEE Conf. on Fuzzy Systems, 481–486

    Google Scholar 

  35. Szmidt E. and Kacprzyk J. (2008) A new approach to ranking alternatives expressed via intuitionistic fuzzy sets. In: D. Ruan et al. (Eds.) Computational Intelligence in Decision and Control. World Scientific, 265–270.

    Google Scholar 

  36. Szmidt E. and Kacprzyk J.: Ranking of Intuitionistic Fuzzy Alternatives in a Multi-criteria Decision Making Problem. In: Proceedings of the conference: NAFIPS 2009, Cincinnati, USA, June 14–17, 2009, IEEE, ISBN: 978-1-4244-4577-6.

    Google Scholar 

  37. Szmidt E., Kacprzyk J. (2011) Intuitionistic fuzzy sets – Two and three term representations in the context of a Hausdorff distance. Acta Universitatis Matthiae Belii, Series Mathematics, available at http://ACTAMTH.SAVBB.SK, Vol.19, No. 19, 2011, 53–62.

  38. Szmidt E. and Kacprzyk J. (2009) Amount of information and its reliability in the ranking of Atanassov’s intuitionistic fuzzy alternatives. In: Recent Advances in decision Making, SCI 222. E. Rakus-Andersson, R. Yager, N. Ichalkaranje, L.C. Jain (Eds.), Springer-Verlag, 7–19.

    Google Scholar 

  39. Szmidt E. and Kacprzyk J. (2010): Correlation between intuitionistic fuzzy sets. LNAI 6178 (Computational Intelligence for Knowledge-Based Systems Design, Eds. E.Hullermeier, R. Kruse, F. Hoffmann), 169–177.

    Google Scholar 

  40. Szmidt E. and Kacprzyk J. (2010): The Spearman rank correlation coefficient between intuitionistic fuzzy sets. In: Proc. 2010 IEEE Int. Conf. on Intelligent Systems IEEE’IS 2010, London, 276–280.

    Google Scholar 

  41. Szmidt E., Kacprzyk J., Bujnowski P. (2011): Measuring the Amount of Knowledge for Atanassov’s Intuitionistic Fuzzy Sets. Fuzzy Logic and Applications, Lecture Notes in Artificial Intelligence, Vol. 6857, 2011, 17–24.

    MATH  Google Scholar 

  42. Szmidt E., Kacprzyk J. and Bujnowski P. (2011) Pearson’s coefficient between intuitionistic fuzzy sets. Notes on Intuitionistic Fuzzy Sets, 17 (2), 25–34.

    MATH  Google Scholar 

  43. Szmidt E. and Kacprzyk J. (2011) The Kendall Rank Correlation between Intuitionistic Fuzzy Sets. In: Proc.: World Conference on Soft Computing, San Francisco, CA, USA, 23/05/2011-26/05/2011.

    Google Scholar 

  44. Szmidt E. and Kacprzyk J. (2011) The Spearman and Kendall rank correlation coefficients between intuitionistic fuzzy sets. In: Proc. 7th conf. European Society for Fuzzy Logic and Technology, Aix-Les-Bains, France, Antantic Press, 521–528.

    Google Scholar 

  45. Szmidt E., Kacprzyk J., Bujnowski P. (2012): Advances in Principal Component Analysis for Intuitionistic Fuzzy Data Sets. 2012 IEEE 6th International Conference ,,Intelligent Systems”, 194–199.

    Google Scholar 

  46. Szmidt E. and Kacprzyk J. (2012) A New Approach to Principal Component Analysis for Intuitionistic Fuzzy Data Sets. S. Greco et al. (Eds.): IPMU 2012, Part II, CCIS 298, 529–538, Springer-Verlag Berlin Heidelberg.

    Google Scholar 

  47. Szmidt E. and Kacprzyk J. (2015) Two and Three Term Representations of Intuitionistic Fuzzy Sets: Some Conceptual and Analytic Aspects. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), Istanbul, Turkey, August 2–5, 2015, IEEE, ss. 1-8.

    Google Scholar 

  48. Szmidt E., Kacprzyk J. and Bujnowski P. (2012) Advances in Principal Component Analysis for Intuitionistic Fuzzy Data Sets. 2012 IEEE 6th International Conference “Intelligent Systems”, 194–199.

    Google Scholar 

  49. Szmidt E., Kacprzyk J. and Bujnowski P. (2012): Correlation between Intuitionistic Fuzzy Sets: Some Conceptual and Numerical Extensions. WCCI 2012 IEEE World Congress on Computational Intelligence, Brisbane, Australia, 480–486.

    Google Scholar 

  50. Szmidt E., Kacprzyk J., Bujnowski P. (2014): How to measure the amount of knowledge conveyed by Atanassov’s intuitionistic fuzzy sets. Information Sciences, 257, 276–285.

    Article  MathSciNet  MATH  Google Scholar 

  51. Szmidt E., Kreinovich V. (2009) Symmetry between true, false, and uncertain: An explanation. Notes on Intuitionistic Fuzzy Sets 15, No. 4, 1–8.

    MATH  Google Scholar 

  52. Szmidt E. and Kukier M. (2006): Classification of Imbalanced and Overlap** Classes using Intuitionistic Fuzzy Sets. IEEE IS’06, London, 722–727.

    Google Scholar 

  53. Szmidt E. and Kukier M. (2008): A New Approach to Classification of Imbalanced Classes via Atanassov’s Intuitionistic Fuzzy Sets. In: Hsiao-Fan Wang (Ed.): Intelligent Data Analysis : Develo** New Methodologies Through Pattern Discovery and Recovery. Idea Group, 85–101.

    Google Scholar 

  54. Szmidt E., Kukier M. (2008): Atanassov’s intuitionistic fuzzy sets in classification of imbalanced and overlap** classes. In: P. Chountas, I. Petrounias, J. Kacprzyk (Eds.): Intelligent Techniques and Tools for Novel System Architectures. Series: Studies in Computational Intelligence, Vol. 109, Springer, Berlin Heidelberg 2008, 455–471.

    Google Scholar 

  55. Tan Ch. and Zhang Q. (2005): Fuzzy multiple attribute TOPSIS decision making method based on intuitionistic fuzzy set theory. IFSA 2005, 1602–1605.

    Google Scholar 

  56. Tasseva V., Szmidt E. and Kacprzyk J. (2005): On one of the geometrical interpretations of the intuitionistic fuzzy sets. Notes on IFS, 11 (3), 21–27.

    Google Scholar 

  57. Zadeh L.A. (1965): Fuzzy sets. Information and Control, 8, 338–353.

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eulalia Szmidt .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Szmidt, E., Kacprzyk, J. (2017). A Perspective on Differences Between Atanassov’s Intuitionistic Fuzzy Sets and Interval-Valued Fuzzy Sets. In: Torra, V., Dahlbom, A., Narukawa, Y. (eds) Fuzzy Sets, Rough Sets, Multisets and Clustering. Studies in Computational Intelligence, vol 671. Springer, Cham. https://doi.org/10.1007/978-3-319-47557-8_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-47557-8_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47556-1

  • Online ISBN: 978-3-319-47557-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Navigation