On Soft Pre-Rough Approximation Space with Applications in Decision Making
- M. El Sayed1,*, Wadia Faid Hassan Al-shameri1, M. A. El Safty2
1
Department of Mathematics, College of Science and Arts, Najran University, Najran, 66445, Saudi Arabia
2 Department of Mathematics and Statistics, College of Science, Taif University, Taif, 21944, Saudi Arabia
* Corresponding Author: M. El Sayed. Email:
(This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
2 Department of Mathematics and Statistics, College of Science, Taif University, Taif, 21944, Saudi Arabia
* Corresponding Author: M. El Sayed. Email:
(This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
Received 02 November 2021; Accepted 20 January 2022; Issue published 27 June 2022
Abstract
A soft, rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data. In the
present work, we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation
space. These concepts are soft pre-rough equality, soft pre-rough inclusion, soft pre-rough belonging, soft predefinability, soft pre-internal lower, and soft pre-external lower. We study the properties of these concepts. Finally,
we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for
Chikungunya medical illnesses. In reality, the impact factors of Chikungunya’s medical infection were determined.
Moreover, we develop two new algorithms to address Chikungunya virus issues. Our proposed approach is sensible
and effective.
Keywords
Soft rough set; soft pre-rough set approach; soft pre-internal lower and soft pre-external upper; soft nowhere dense set and Chikungunya medical application; intelligence discovery
Cite This Article
Sayed, M. E., Faid, W., A., M. (2022). On Soft Pre-Rough Approximation Space with Applications in Decision Making. CMES-Computer Modeling in Engineering & Sciences, 132(3), 865–879.
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