On Improper m- Polar Soft Fuzzy Graph and its Application for Medical Diagnosis in the Current COVID-19 Scenario

S Ramkumar; R Sridevi

doi:10.17485/IJST/v16i34.1034

Article

On Improper m- Polar Soft Fuzzy Graph and its Application for Medical Diagnosis in the Current COVID-19 Scenario

VIEWS 492
PDF 122

Indian Journal of Science and Technology

DOI: 10.17485/IJST/v16i34.1034

Year: 2023, Volume: 16, Issue: 34, Pages: 2681-2692

Original Article

On Improper m- Polar Soft Fuzzy Graph and its Application for Medical Diagnosis in the Current COVID-19 Scenario

S Ramkumar^1,2*, R Sridevi^3,2

¹Research Scholar, Sri S. Ramasamy Naidu Memorial College, Affiliated to Madurai Kamaraj University, Palkalai Nagar, Madurai, Sattur, 626 203, Tamil Nadu, India
²PG and Research Department of Mathematics, Sri S. Ramasamy Naidu Memorial College,
Affiliated to Madurai Kamaraj University, Palkalai Nagar, Madurai, Sattur, 626 203, TamilNadu, India
³Assistant Professor, Sri S. Ramasamy Naidu Memorial College, Affiliated to Madurai Kamaraj University, Palkalai Nagar, Madurai, Sattur, 626 203, Tamil Nadu, India

*Corresponding Author
Email: [email protected]

Received Date:03 May 2023, Accepted Date:01 August 2023, Published Date:08 September 2023

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

Abstract

Objectives: To introduce the concepts of improper m􀀀 polar soft fuzzy graphs and related terms. Methods: An algorithm has been established to apply m􀀀 polar soft fuzzy graph to make a decision for medical diagnosis in the current COVID-19 scenario. It has been demonstrated with examples. Findings: The newly integrated ideas of the soft sets and m􀀀 polar fuzzy sets will lead to numerous prospective applications in the m􀀀 polar fuzzy set theoretical domain by adding extra fuzziness in analysing. m􀀀 polar soft sets that are most useful in practical applications. The concepts such as improper m􀀀 polar soft fuzzy graphs, totally improper m􀀀 polar soft fuzzy graphs, neighbourly improper m􀀀 polar soft fuzzy graphs, neighbourly totally improper m􀀀 polar soft fuzzy graphs, highly improper m􀀀 polar soft fuzzy graphs and highly totally improper m􀀀 polar soft fuzzy graphs are defined. Novelty: The identical condition of neighbourly improper 3 - polar soft fuzzy graphs and highly improper 3-polar soft fuzzy graphs are discussed and validated. Various results related to these concepts have been established

Keywords: Improper; Totally Improper; Neighbourly Improper; Neighbourly Totally Improper; Highly Improper m- Polar Soft Fuzzy Graphs

References

Akram M, Shahzadi S. Novel intuitionistic fuzzy soft multiple-attribute decision-making methods. Neural Computing and Applications. 2018;29(7):435–447. Available from: https://doi.org/10.1007/s00521-016-2543-x
Bera S, Pal M. On m Polar Interval-valued Fuzzy Graph and its Application. Fuzzy Information and Engineering. 2020;12(1):71–96. Available from: https://doi.org/10.1080/16168658.2020.1785993
Bera S, Pal M. A novel concept of domination in m-polar interval-valued fuzzy graph and its application. Neural Computing and Applications. 2022;34(1):745–756. Available from: https://doi.org/10.1080/16168658.2020.1785993
Khan M, Kumam P, Ashraf S, Kumam W. Generalized Picture Fuzzy Soft Sets and Their Application in Decision Support Systems. Symmetry. 2019;11(3):415. Available from: https://doi.org/10.3390/sym11030415
Liu P, Chen SM, Wang Y. Multi attribute group decision making based on intuitionistic. 2017. Available from: https://doi.org/10.1016/j.ins.2017.05.016
Mondal U, Mahapatra T, Xin Q, Pal M. Solution of road network problem with the help of m-polar fuzzy graph using isometric and antipodal concept. 2023. Available from: https://doi.org/10.1038/s41598-023-33071-9
Meenakshi A, Armstrong N, Malar S. Mathematical Model of Anaysation of COVID-19 using Graphs. AIP Conference Proceedings . 2022. Available from: https://doi.org/10.1063/5.0109199
Muhiuddin G, Mahapatra T, Pal M, Alshahrani O, Mahboob A. Integrity on m-Polar Fuzzy Graphs and Its Application. 2023. Available from: https://doi.org/10.3390/math11061398
Mohanty RK, Tripathy B. An improved approach to group decision-making using intuitionistic fuzzy soft set. 2021. Available from: https://doi.org/10.1007/978-981-15-4218-328
Ramkumar S, Sridevi R. , Proper m-Polar Soft Fuzzy Graphs. Advances in Mathematics: Scientific Journal. 2021;10(4):1845–1856. Available from: https://doi.org/10.37418/amsj.10.4.1
Ramkumar S, Sridevi R. Domination in m-polar soft fuzzy graphs. 2023. Available from: https://doi.org/10.23755/rm.v46i0.1070
Sultana F, Gulistan M, Ali M, Yaqoob N, Khan M, Rashid T, et al. A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally. 2022. Available from: https://doi.org/10.1007/s12652-022-03772-6
Saeed M, Harl MI, Saeed MH, Mekawy I. Theoretical framework for a decision support system for micro-enterprise supermarket investment risk assessment using novel picture fuzzy hypersoft graph. PLOS ONE. 18(3):e0273642. Available from: https://doi.org/10.1371/journal.pone.0273642

Copyright

© 2023 Ramkumar & Sridevi. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)