Journal of Neutrosophic and Fuzzy Systems

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https://doi.org/10.54216/JNFS

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Journal of Neutrosophic and Fuzzy Systems

Volume 2 , Issue 1 , PP: 31-39, 2022 | Cite this article as | XML | Html | PDF

Data with Rough Attributes and Its Reduct Analysis

Prem Kumar Singh 1 *

  • 1 Department of Computer Science and Engineering, Gandhi Institute of Technology and Management-Visakhapatnam, Andhra Pradesh 530045, India - (premsingh.csjm@gmail.com)
  • Doi: https://doi.org/10.54216/JNFS.020104

    Received July 26, 2021 Accepted: Jan 08, 2022
    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

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    Cite This Article As :
    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)
    Prem Kumar Singh. (2022). Data with Rough Attributes and Its Reduct Analysis. Journal of , 2 ( 1 ), 31-39 (Doi   :  https://doi.org/10.54216/JNFS.020104)
    Prem Kumar Singh. "Data with Rough Attributes and Its Reduct Analysis." Journal of , 2 no. 1 (2022): 31-39 (Doi   :  https://doi.org/10.54216/JNFS.020104)
    Prem Kumar Singh. (2022). Data with Rough Attributes and Its Reduct Analysis. Journal of , 2 ( 1 ), 31-39 (Doi   :  https://doi.org/10.54216/JNFS.020104)
    Prem Kumar Singh. Data with Rough Attributes and Its Reduct Analysis. Journal of , (2022); 2 ( 1 ): 31-39 (Doi   :  https://doi.org/10.54216/JNFS.020104)
    Prem Kumar Singh, Data with Rough Attributes and Its Reduct Analysis, Journal of , Vol. 2 , No. 1 , (2022) : 31-39 (Doi   :  https://doi.org/10.54216/JNFS.020104)