A New Approach of Functional Dependency in a Neutrosophic Relational Database Model
Author : Soumitra De and Jaydev MishraVolume 8 No.2 April-June 2019 pp 44-48
Abstract
In order to model the imprecise and uncertain information, different classical relational data model have been studied in literature using vague set theory. However, neutrosophic set, as a generalized vague set, has more powerful ability to process fuzzy information than vague set. In this paper, we have proposed a neutrosophic relational database model and have defined a new kind of neutrosophic functional dependency (called -nfd) based on the -equality of tuples and the similarity measure of neutrosophic sets. Next, we present a set of sound neutrosophic inference rules which are similar to Armstrong’s axioms for the classical case. Finally, partial -nfdand neutrosophic key have been studied with the new notion of -nfdand also tested.
Keywords
Neutro-sophicSet, Similarity Measure of Neutrosophic Data, Neutro-sophic Functional Dependency( -Nfd),Partial -Nfd, Neutro-sophic Key
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References
[1] F. Smarandache, “First International Conference on Neutrosophy, Neutrosophic Probability, Set, and Logic”, University of New Mexico, Vol. 1, No. 3, 2001.
[2] F. Zhao, Z. M. Ma and L. Yan, “A Vague Relational Model and Algebra”, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD2007), Vol. 1, pp. 81-85, 2007.
[3] F. Zhao and Z. M. Ma, “Vague Query Based on Vague Relational Model”, Springer- Verlag Berlin Heidelberg, AISC 61, pp. 229-238, 2009.
[4] Deli and S. Broumi, “Neutrosophic soft relations and some properties”, Annals of Fuzzy Mathematics and Informatics, Vol. 9, No. 1, pp. 169–182, 2015.
[5] J. Mishra and S. Ghosh, “A New Functional Dependency in a Vague Relational Database Model”, International Journal of Computer Applications , Vol. 39, No. 8, pp. 29-33, 2012.
[6] J. Mishra , S. Ghosh, “A Vague Multivalued Data Dependency”, International Journal of Fuzzy Information and Engineering, Springer, Vol. 5, No. 4, pp. 459-473,2013.
[7] J. Mishra and S. Ghosh, “Uncertain Query Processing using Vague Sets or Fuzzy Set: Which one isBetter?”,International Journal of Computers, Communications and Control (IJCCC), Vol. 9, No. 6, pp. 730-740, 2014.
[8] M. Arora and R. Biswas, “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.
[9] M. Arora, R. Biswas and U.S. Pandy, “Neutrosophic Relational Database Decomposition”, International Journal of Advanced Computer Science and Applications, Vol. 2, No. 8, pp.121-125, 2011.
[10] S. Broumi, “Generalized Neutrosophic Soft Set”, International Journal of Computer Science, Engineering and Information Technology, Vol. 3, No. 2, pp. 17–30, 2013.
[11] S. De and J. Mishra “Handle Inconsistent Data using New Method of Neutrosophic Logic for Proper Outcome”, International Journal of Science , technology and Management,Vol. 6, No. 2, pp. 383-387, 2017.
[12] S. De and J. Mishra “Query Processing of Inconsistent Data using NeutrosophicSet”, IEEE International Conference on Computing Communication and Automation, Vol. 10, No. 6, pp. 120-124, 2016.
[13] S. De and J. Mishra “Compare Different Similarity Measure Formula Based Imprecise Query on Neutrosophic Data”, International Conference on Advanced Computing and Intelligent Engineering, Vol.5, No.12, pp. 330-334, 2016.
[14] S. De and J. Mishra “Inconsistent Data Processing Using Vague Set and Neutrosophic Set for Justifying Better Outcome”, IEEE International Conference on Inventive Communication and Computational Technologies, Vol.7, No. 4, pp. 26-30, 2017.
[15] S. De and J. Mishra “Processing of Inconsistent Neutrosophic Data and Selecting Primary Key from the Relation” International Conference on Inventive Computing and Informatics, Vol.6, No. 7, pp. 245-250, 2017.
[16] W. L. Gau and D. J. Buehrer, “Vague Sets”, IEEE Trans. Syst. Man, Cybernetics, Vol. 23, No. 2, pp.610- 614,1993.