Decision Making Using Rough Topology and Indiscernibility Matrix for Corona Virus Diagnosis

Authors

  • Kanchana. M  PG, Mathematics, Dr. SNS Rajalakshmi College of Arts and Science, Coimbatore, Tamil Nadu, India
  • Rekha. S  Assistant professor, Dr. SNS Rajalakshmi College of Arts and Science, Coimbatore, Tamil Nadu, India

DOI:

https://doi.org//10.32628/IJSRSET20724

Keywords:

Rough sets, Set Approximation, Basis, Indiscernibility Matrix

Abstract

Rough set theory is a new mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge. In recent years the research and applications on rough set theory have attracted more. In this paper, we have introduced and analyze the Rough set theory and also decide the factors for corona virus diagnosis by using Indiscernibility matrix.

References

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  2. Nirmala Rebecca Paul, "Rough Topology Based Decision Making in Medical Diagnosis", International Journal of Mathematics Trends and Technology – Volume 18 Number 1 – Feb 2015
  3. Silvia Rissino and Germano Lambert-Torres, "Rough Set Theory – Fundamental Concepts, Principals, Data Extraction, and Applications".
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  5. Pawlak, Z., "Rough sets," International Journal of Computer and Information Sciences, 11, pp. 341-356, 1982.
  6. Salama,A.S., "Some topological properties of rough sets with tools for data mining", IJCSI International Journal of Computer Science issues 8 (2011) 588-595.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2020-04-30

Issue

Volume 7, Issue 2, March-April-2020

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Kanchana. M, Rekha. S, " Decision Making Using Rough Topology and Indiscernibility Matrix for Corona Virus Diagnosis, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 2, pp.31-33, March-April-2020. Available at doi : https://doi.org/10.32628/IJSRSET20724