Volume 15 • Issue 2 • PP: 98-112 • 2021
Single-valued Plithogenic graph for handling multi-valued attribute data and its context
View PDF Abstract
Recently, several researchers paid attention towards dealin with uncertainty in data with neutrosophic attributes. In this process, a problem is addressed while dealing with contradiction and its impact on decision making. It is considered as one of the major issues for data science researchers working in three-way fuzzy concept lattice. To deal with this issue, current paper tried to introduce the algebra of single-valued Plithogenic graph and its visualization based on infium and supremum. The proposed method also demonstated with an illustrative example for better understanding.
Keywords
References
[1] Multi–granular based n–valued neutrosophic contexts analysis” Granular Computing, 5(3), pp. 287-301, 2020.
[2] S. Gayen, F. Smarandache, S. Jha, M. K. Singh, S. Broumi, R. Kumar “Introduction of Plithogenic hypersot subgroup”. Neutrosophic Sets and Systems, 33, pp. 208-233, 2020.
[3] P. K. Singh “Turiyam set a fourth dimension data representation”. Journal of Applied Mathematics and Physics, 9(7), pp. 1821-1828, 2021.
[4] P. K. Singh “Fourth dimension data representation and its analysis using Turiyam Context”. Journal of Computer and Communications, 9(6), pp. 222-229, 2021.
[5] F. Smarandache “Neutrosophy. Neutrosophic probability, set, and logic”. ProQuest Information and Learning[M]. Ann Arbor, Michigan, USA, 1998.
[6] P. K. Singh “Three-way fuzzy concept lattice representation using neutrosophic set”. International Journal of Machine Learning and Cybernetics, 8(1), pp. 69-79, 2017.
[7] P. K. Singh “Three-way n-valued neutrosophic concept lattice at different granulation”. International Journal of Machine Learning and Cybernetics, 9(11), pp. 1839-1855, 2018.
[8] F. Smarandache, “Plithogeny, Plithogenic Set, Logic, Probability, and Statistics”. In: Pons Publishing House, Brussels 2017.
[9] F. Smarandache “Extension of Soft Set to hyperSoft Set, and then to Plithogenic Hypersoft set”. Neutrosophic Set and System, 22, pp. 168-170, 2018.
[10] Prem Kumar Singh “Plithogenic set for multi-variable data analysis”. International Journal of Neutrosophic Sciences, 1(2), pp. 81-89, 2020. .
[11]S. Rana, M. Qayuum, M. Saeed, F. Smarandache, B.A. Khan “Plithogenic fuzzy, whole hypersoft set, construction of operators and their application in frequency matrix multi attribute decision making technique”. Neutrosophic Sets and Systems, 28, pp. 34-50, 2019.
[12] P. K. Singh “Complex multi-–fuzzy context analysis at different granulation”. Granular Computing, 6(1), pp. 191-206.
[13] S. P. Priyadharsini, I. Nirmala, F. Smarandache “Plithogenic Cubic Set”. International Journal of Neutrosophic Sciences 11(1), pp. 30-38, 2020.
[14]M. Nivetha, F. Smarandache “Introduction to Combined Plithogenic Hypersoft Sets”. Neutrosophic Sets and Systems, 35, pp. 503-510, 2020.
[15]S.Gomathy, D. Nagarajan, S. Broumi, M. Lathamaheswari “Plithogenic sets and their application in decision making”. Neutrosophic Sets and Systems, 83, pp. 453-469, 2020.
[16]S. Broumi, F. Smarandache, M. Talea, A. Bakali “Single valued neutrosophic graphs: Degree, order and size”. In: Proceedings of 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 2444-2451, 2016.
[17] M. Dehmer, F. Emmert-Streib, Y. Shi “Quantitative Graph Theory: A new branch of graph theory and network science”. Information Sciences, 418-419, pp. 575-580, 2017.
[18]P. K. Singh “Complex neutrosophic δ-equal concepts and their applications in water healthcare”. In: Data Analytics in Biomedical Engineering and Healthcare, pp. 233-267, 2021.
[19]N Martin, F. Smaraandache “Concentric Plithogenic Hypergraph based on Plithogenic Hypersoft sets – A Novel Outlook”. Neutrosophic Sets and Systems, 33, pp. 78-91, 2020.
[20]W. B. Vasantha Kandasamy, Ilanthenral K, Florentin Smarandache “Plithogenic graph”. Infinite study, Indo American book, 2020.
Cite This Article
Choose your preferred format