1
Department of Computer Science and Engineering, Gandhi Institute of Technology and Management-Visakhapatnam, Andhra Pradesh 530045, India
(premsingh.csjm@gmail.com)
Abstract :
Recent time many researchers focused on dealing the uncertainty and its characterization. The precise approximation of uncertainty in many-valued data set is one of the major tasks. It becomes more difficult in case the given data sets are non-Euclidean. Hence the rough fuzzy set and its graphical visualization is introduced in this paper for knowledge processing tasks.
Keywords :
Fuzzy Rough graph , Knowledge representation , Many-valued attributes , Non-Euclidean geometry , Rough Set , Rough graph
References :
[1] Singh P. K., “Three-way fuzzy concept lattice representation using neutrosophic set”, International Journal of Machine Learning and Cybernetics, Vol 8, Issue 1, pp. 69-79, 2017.
[2] Singh PK, Ch. Aswani Kumar, “Concept lattice reduction using different subset of attributes as information granules”, Granular Computing, Vol. 2, Issue 3), pp. 159–173, 2017
[3] Singh PK, “AntiGeometry and NeutroGeometry characterization of Non-Euclidean data sets”, Journal of Neutrosophic and Fuzzy Systems, Vol 1, Issue 1, pp. 24-33, DOI: https://doi.org/10.54216/JNFS.0101012
[4] Singh PK, “Data with Non-Euclidean Geometry and its Characterization,” Journal of Artificial Intelligence and Technology, 2021, Vol. 2, Issue 1, pp-3-8., DOI: 10.37965/jait.2021.12001
[5] Singh PK, “Cubic graph representation of concept lattice and its decomposition”, Evolving System, doi: 10.1007/s12530-021-09400-6
[6] Pawlak Z, “Rough sets”, Int. J. Comput. Inf. Sci. Vol., pp. 341–356, 1982
[7] Pawlak Z, “Rough set theory and its applications to data analysis,” Cybern Syst Vol. 29, Issue 7, pp. 661–688, 1998
[8] He T, Chan Y, Shi K, “Weighted rough graph and its application,” In: Proceedings of IEEE Sixth Int Conf Intell Syst Des Appl 1:486–492, 2006
[9] He T, “Rough properties of rough graph,” Appl Mech Mater Vol 157–158, pp. 517–520, 2012
[10] He T, “Representation form of rough graph,” Appl Mech Mater, Vol. 157–158, pp. 874–877, 2012
[11] Liang M, Liang B, Wei L, Xu X, “Edge rough graph and its application,” In: Proc. Of eighth International Conference on Fuzzy Systems and Knowledge Discovery 2011, pp. 335–338
[12] Wang S, Zhu Q, Zhu W, Min F, “Graph and matrix approaches to rough sets through matroids. Information Sciences, Vol. 288, pp. 1–11, 2014
[13] Li W, Huang Z, Jia X, Cai X, “Neighborhood based decision-theoretic rough set models,” International Journal of Approximate Reasoning, Vol. 69, pp. 1–17, 2016
[14] Noor R, Irshad I, Javaid I, “Soft rough graphs”. arXiv preprint arXiv:1707.05837, 2017
[15] Fariha Z, Akram M, “A novel decision–making method based on rough fuzzy information,” Int J Fuzzy Syst Vol. 20, Issue 3, pp. 1000–1014, 2018
[16] Rehman N, Shah N, Ali MI, Park C, “Uncertainty measurement for neighborhood based soft covering rough graphs with applications,” RACSAM, Vol. 113, pp. 2515–2535, 2019
[17] Mathew B, John SJ, Garg H, “Vertex rough graphs,” Complex Intell. Syst. Vol 6, pp. 347– 353, 2020
[18] Yao YY, “Relational interpretations of neighborhood operators and rough set approximation operators,” Inf. Sci., Vol. 101, pp. 239–259, 1998
[19] Yao YY, “Three-way decisions with probabilistic rough sets,” Inf. Sci., Vol. 180, pp. 341–353, 2010
| Style | # |
|---|---|
| MLA | Prem Kumar Singh. "Data with Rough Attributes and Its Reduct Analysis." Full Length Article, Vol. 2, No. 1, 2022 ,PP. 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |
| APA | Prem Kumar Singh. (2022). Data with Rough Attributes and Its Reduct Analysis. Journal of Full Length Article, 2 ( 1 ), 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |
| Chicago | Prem Kumar Singh. "Data with Rough Attributes and Its Reduct Analysis." Journal of Full Length Article, 2 no. 1 (2022): 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |
| Harvard | Prem Kumar Singh. (2022). Data with Rough Attributes and Its Reduct Analysis. Journal of Full Length Article, 2 ( 1 ), 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |
| Vancouver | Prem Kumar Singh. Data with Rough Attributes and Its Reduct Analysis. Journal of Full Length Article, (2022); 2 ( 1 ): 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |
| IEEE | Prem Kumar Singh, Data with Rough Attributes and Its Reduct Analysis, Journal of Full Length Article, Vol. 2 , No. 1 , (2022) : 31-39 (Doi : https://doi.org/10.54216/JNFS.020104) |