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Proceedings of the Second International Conference on Computer and Communication Technologies pp 387–399Cite as

Intuitionistic Fuzzy Similarity and Information Measures with Physical Education Teaching Quality Assessment

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 379))

Abstract

Information and similarity measures have a vital place in the fuzzy set theory. It has been investigated by many researchers with different aspects. In this paper, new intuitionistic fuzzy similarity and information measures based on sine function are proposed. Comparison of proposed information measures with the existing ones is listed. Numerical results clearly indicate the efficiencies of these measures over others. New technique for multi-criteria decision-making (MCDM) quandaries to rank the alternatives is introduced. This technique is developed on the application intuitionistic fuzzy information measure and weighted averaging operator (IFWAO). A case of five colleges ranking of a district region is studied and discussed.

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References

  1. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  2. Grzegorzewski, P.: On possible and necessary inclusion of intuitionistic fuzzy sets. Inf. Sci. 181, 342–350 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  3. Atanassov, K.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  4. Mishra, A.R., Jain, D., Hooda, D.S.: Exponential intuitionistic fuzzy information measure with assessment of service quality. Communicated (2015)

    Google Scholar 

  5. Mishra, A.R., Jain, D., Hooda, D.S.: Intuitionistic fuzzy information with application in rating of township development. Communicated (2015)

    Google Scholar 

  6. Castineira, E.E., Cubillo, S., Montilla, W.: Measuring incompatibility between Atanassovs intuitionistic fuzzy sets. Inf. Sci. 180, 820–833 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  7. Liu, H.W., Wang, G.J.: Multi-criteria decision-making methods based on intuitionistic fuzzy sets. Eur. J. Oper. Res. 179, 220–233 (2007)

    Article  MATH  Google Scholar 

  8. Xu, Z.H.: Intuitionistic preference relations and their application in group decision making. Inf. Sci. 177, 2363–2379 (2007)

    Article  MATH  Google Scholar 

  9. Xu, Z.H., Chen, J., Wu, J.J.: Clustering algorithm for intuitionistic fuzzy sets. Inf. Sci. 178, 3775–3790 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  10. Szmidt, E., Kacprzyk, J.: Distances between intuitionistic fuzzy sets. Fuzzy Sets Syst. 114, 505–518 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  11. Wang, W.Q., Xin, X.L.: Distance measure between intuitionistic fuzzy sets. Pattern Recogn. Lett. 26, 2063–2069 (2005)

    Article  Google Scholar 

  12. Wang, P.Z.: Fuzzy Sets and Its Applications. Shanghai Science and Technology Press, Shanghai (1983)

    MATH  Google Scholar 

  13. Wang, X.Z., De Baets, B., Kerre, E.: A comparative study of similarity measures. Fuzzy Sets Syst. 73, 259–268 (1995)

    Article  MATH  Google Scholar 

  14. Mitchell, H.B.: On the Dengfeng-Chuntian similarity measure and its application to pattern recognition. Pattern Recogn. Lett. 24, 3101–3104 (2003)

    Article  Google Scholar 

  15. Hwang, C.L., Yoon, K.S.: Multiple Attribute Decision Making: Methods and Applications. Springer, Berlin (1981)

    Book  MATH  Google Scholar 

  16. Joshi, D., Kumar, S.: Intuitionistic fuzzy entropy and distance measure based TOPSIS method for multi-criteria decision making. Egypt. Inf. J. 15, 97–104 (2014)

    Article  Google Scholar 

  17. Lin, L., Yuan, X.H., Xia, Z.Q.: Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets. J. Comput. Syst. Sci. 73, 84–88 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  18. Yue, Z.: Extension of TOPSIS to determine weight of decision maker for group decision making problems with uncertain information. Exp. Syst. Appl. 39, 6343–6350 (2012)

    Article  Google Scholar 

  19. Xu, Z.S.: Intuitionistic fuzzy aggregation operators. IEEE Trans. Fuzzy Syst. 15(6), 1179–1187 (2007)

    Article  Google Scholar 

  20. Szmidt, E., Kacprzyk, J.: Entropy for intuitionistic fuzzy sets. Fuzzy Sets Syst. 118, 467–477 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  21. Vlachos, I.K., Sergiagis, G.D.: Intuitionistic fuzzy information—application to pattern recognition. Pattern Recogn. Lett. 28, 197–206 (2007)

    Article  Google Scholar 

  22. Wei, C., Zhang, Y.: Entropy measures for interval-valued intuitionistic fuzzy sets and their application in group decision making. Math. Probl. Eng. 2015, 1–13 (2015)

    Google Scholar 

  23. Fan, H.: An approach to evaluating the physical education teaching quality of higher education institution with uncertain information. JDCTA 6, 419–425 (2012)

    Google Scholar 

  24. Pang, M.: An approach to evaluating the physical education teaching quality of higher education institution with intuitionistic fuzzy information. JCIT 7, 164–170 (2012)

    Google Scholar 

  25. Chen, Z.P., Yang, W.: A new multiple attribute group decision making method in intuitionistic fuzzy setting. Appl. Math. Model. 35, 4424–4437 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  26. Chen, S.M., Tan, J.M.: Handling multi-criteria fuzzy decision making problems based on vague set theory. Fuzzy Sets Syst. 67, 163–172 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  27. Hong, D.H., Choi, C.H.: Multicriteria fuzzy decision making problems based on vague set theory. Fuzzy Sets Syst. 114, 103–113 (2000)

    Article  MATH  Google Scholar 

  28. Wu, J.Z., Zhang, Q.: Multicriteria decision making method based on intuitionistic fuzzy weighted entropy. Expert Syst. Appl. 38, 916–922 (2011)

    Article  Google Scholar 

  29. Grzegorzewski, P., Mrowka, E.: Some notes on (Attnassov’s) intuitionistic fuzzy sets. Fuzzy Sets Syst. 156, 492–495 (2005)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, 473226, M.P., India

    Arunodaya Raj Mishra, Divya Jain & D. S. Hooda

Authors
  1. Arunodaya Raj Mishra
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  2. Divya Jain
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  3. D. S. Hooda
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Corresponding author

Correspondence to Arunodaya Raj Mishra .

Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

  2. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Mishra, A.R., Jain, D., Hooda, D.S. (2016). Intuitionistic Fuzzy Similarity and Information Measures with Physical Education Teaching Quality Assessment. In: Satapathy, S., Raju, K., Mandal, J., Bhateja, V. (eds) Proceedings of the Second International Conference on Computer and Communication Technologies. Advances in Intelligent Systems and Computing, vol 379. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2517-1_38

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  • DOI: https://doi.org/10.1007/978-81-322-2517-1_38

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2516-4

  • Online ISBN: 978-81-322-2517-1

  • eBook Packages: EngineeringEngineering (R0)

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