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Neutrosophic Logic Based New Methodology to Handle Indeterminacy Data for Taking Accurate Decision

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 410)

Abstract

We proposed a method using Neutrosophic set and data to take the most suitable decision with the help of three different members truth, indeterminacy and falsity. Neutrosophic logic is capable of handling indeterministic and inconsistent information. We have focused to draw a meaning full outcome using neutrosophic concept about the illness of a patient who is suffering from a disease. Fuzzy logic can only handle incomplete information using truth membership value. Vague logic also can handle incomplete information using truth and false membership values. It is an upgrade part of fuzzy and vague concept.

Keywords

Neutrosophic logic Neutrosophic set Neutrosophic operation New method 

References

  1. 1.
    Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Raju, K.V.S.V.N., Majumdar, A.K.: Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database system. ACM Trans. Database Syst. 13(2), 129–166 (1988)CrossRefGoogle Scholar
  3. 3.
    Sözat, M.I., Yazici, A.: A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations. Fuzzy Sets Syst. 117(2), 161–181 (2001)MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Bahar, O., Yazici, A.: Normalization and lossless join decomposition of similarity-based fuzzy relational databases. Int. J. Intell. Syst. 19(10), 885–917 (2004)CrossRefMATHGoogle Scholar
  5. 5.
    Gau, W.L., Buehrer, D.J.: Vague Sets. IEEE Trans. Syst. Man Cybern. 23(2), 610–614 (1993)CrossRefMATHGoogle Scholar
  6. 6.
    Zhao, F., Ma, Z.M., Yan, L.: A vague relational model and algebra. In: Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 1:81–85 (2007)Google Scholar
  7. 7.
    Zhao, F., Ma, Z.M.: Vague query based on vague relational model. In: AISC 61, pp. 229–238, Springer, Berlin (2009)Google Scholar
  8. 8.
    Mishra, J., Ghosh, S.: A new functional dependency in a vague relational database model. Int. J. Comput. Appl. (IJCA) 39(8), 29–33 (2012)Google Scholar
  9. 9.
    Mishra, J., Ghosh, S.: A vague multivalued data dependency. Int. J. Fuzzy Inform. Eng. 5(4), 459–473 (2013). ISSN: 1616-8666 (Springer)Google Scholar
  10. 10.
    Mishra, J., Ghosh, S.: Uncertain query processing using vague sets or fuzzy set: which one is better? Int. J. Comput. Commun. Control (IJCCC) 9(6), 730–740 (2014)CrossRefGoogle Scholar
  11. 11.
    Smarandache, F.: First International Conference on Neutrosophy, Neutrosophic Probability, Set, and Logic, University of New Mexico, vol. 1, no. 3 (2001)Google Scholar
  12. 12.
    Smarandache, F.: A unifying field in logics: neutrosophic logic, in multiple-valued logic. Int. J. 8(3), 385–438 (2002)Google Scholar
  13. 13.
    Smarandache, F.: Definitions derived from neutrosophics, multiple-valued logic. Int. J. 8(5–6), 591–604 (2002)MathSciNetMATHGoogle Scholar
  14. 14.
    Arora, M., Biswas, R.: Deployment of neutrosophic technology to retrieve answers for queries posed in natural language. In: 3rd International Conference on Computer Science and Information Technology ICCSIT 2010, vol. 3, pp. 435–439 (2010)Google Scholar
  15. 15.
    Arora, M., Biswas, R., Pandy, U.S.: Neutrosophic relational database decomposition. Int. J. Adv. Comput. Sci. Appl. 2(8), 121–125 (2011)Google Scholar
  16. 16.
    Broumi, S.: Generalized neutrosophic soft set. Int. J. Comput. Sci. Eng. Inform. Technol. 3(2), 17–30 (2013)CrossRefGoogle Scholar
  17. 17.
    Deli, I., Broumi, S.: Neutrosophic soft relations and some properties. Ann. Fuzzy Math. Inform. 9(1), 169–182 (2015)MathSciNetMATHGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Computer Science & Engineering DepartmentCollege of Engineering and ManagementPurba MedinipurIndia

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