Skip to main content

A New Similarity Measure for Intuitionistic Fuzzy Sets

  • Conference paper
Intelligent Information and Database Systems (ACIIDS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9621))

Included in the following conference series:

  • 2321 Accesses

Abstract

Although there exist many similarity measures for intuitionistic fuzzy sets (IFSs), most of them can not satisfy the axioms of similarity measure or provide reasonable results. In this paper, a review of existing similarity measures for IFSs and their drawbacks is carried out. Then a new similarity measure between IFSs on the base of their knowledge measures is proposed. A comprehensive analysis of the performance features of the proposed measure is conducted in a comparative example. Finally, the proposed similarity measure is employed in application to the turbine fault diagnosis. We point out that the new proposed similarity measure overcomes the drawbacks of the existing similarity measures and gives reliable results in real world application.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping 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.: Intuitionistic Fuzzy Sets. Fuzzy Sets Systems 20(1), 87–96 (1986)

    Article  MathSciNet  Google Scholar 

  2. Atanassov, K.T.: Intuitionistic Fuzzy Sets. Springer, New York (1999)

    Book  MATH  Google Scholar 

  3. Boran, F.R., Akay, D.: A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition. Inf. Sci. 255, 45–57 (2014)

    Article  MathSciNet  MATH  Google Scholar 

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

    Google Scholar 

  5. Chen, S.M.: Measures of similarity between vague sets. Fuzzy Sets Syst. 74(2), 217–223 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  6. Dengfeng, L., Chuntian, C.: New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recognit. Lett. 23(1–3), 221–225 (2002)

    Article  MATH  Google Scholar 

  7. Hong, D.H., Kim, C.: A note on similarity measures between vague sets and between elements. Inf. Sci. 115(1–4), 83–96 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  8. Hung, W.L., Yang, M.S.: Similarity measures of intuitionistic fuzzy sets based on the Hausdorff distance. Pattern Recognit. Lett. 25(14), 1603–1611 (2004)

    Article  Google Scholar 

  9. Li, D.F., Cheng, C.: New similarity measures of intuitionistic fuzzy sets and application to pattern recognition. Pattern Recognit. Lett. 23, 221–225 (2002)

    Article  MATH  Google Scholar 

  10. Li, F., Xu, Z.: Similarity measures between vague sets. J. Softw. 12(6), 922–927 (2001)

    Google Scholar 

  11. Li, Y.H., Olson, D.L., Qin, Z.: Similarity measures between intuitionistic fuzzy (vague) sets: A comparative analysis. Pattern Recognit. Lett. 28, 278–285 (2007)

    Article  Google Scholar 

  12. Liang, Z., Shi, P.: Similarity measures on intuitionistic fuzzy sets. Pattern Recognit. Lett. 24(15), 2687–2693 (2003)

    Article  MATH  Google Scholar 

  13. Liu, H.W.: New similarity measures between intuitionistic fuzzy sets and between elements. Math. Comput. Model. 42, 61–70 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  14. Lu, Z.K., Ye, J.: Cosine similarity measure between vague sets and its application of fault diagnosis. Res. J. Appl. Sci. Eng. Technol. 6(14), 2625–2629 (2013)

    Google Scholar 

  15. Mitchell, H.B.: On the Dengfeng-Chuntian similarity measure and its application to pattern recognitions. Pattern Recognit. Lett. 24(16), 3101–3104 (2003)

    Article  Google Scholar 

  16. Miaoying, T.: A new fuzzy similarity measure based on cotangent function for medical diagnosis. Adv. Model. Optim. 15(2), 151–156 (2013)

    Google Scholar 

  17. Nguyen, H.: A new knowledge-based measure for intuitionistic fuzzy sets and its application in multiple attribute group decision making. Expert Syst. Appl. 42, 8766–8774 (2015)

    Article  Google Scholar 

  18. Shi, L.L., Ye, J.: Study on fault diagnosis of turbine using an improved cosine similarity measure of vague sets. J. Appl. Sci. 13(10), 1781–1786 (2013)

    Article  Google Scholar 

  19. Song, Y., Wang, X., Lei, L., Xue, A.: A new similarity measure between intuitionistic fuzzy sets and its application to pattern recognition. Appl. Intell. 42, 252–261 (2015)

    Article  Google Scholar 

  20. Szmidt, E., Kacprzyk, J.: Geometric similarity measures for the intuitionistic fuzzy sets. In: 8th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2013), pp. 840–847 (2013)

    Google Scholar 

  21. Tan, C., Chen, X.: Dynamic similarity measures between intuitionistic fuzzy sets and its application. Int. J. Fuzzy Syst. 16(4), 511–519 (2014)

    MathSciNet  Google Scholar 

  22. Ye, J.: Fault diagnosis of turbine based on fuzzy cross entropy of vague sets. Expert Syst. Appl. 36, 8103–8106 (2009)

    Article  Google Scholar 

  23. Ye, J.: Cosine similarity measures for intuitionistic fuzzy sets and their applications. Math. Comput. Model. 53(1–2), 91–97 (2011)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hoang Nguyen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nguyen, H. (2016). A New Similarity Measure for Intuitionistic Fuzzy Sets. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_55

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49381-6_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49380-9

  • Online ISBN: 978-3-662-49381-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics