@Article{cmes.2022.020066,
AUTHOR = {M. El Sayed, Wadia Faid Hassan Al-shameri, M. A. El Safty},
TITLE = {On Soft Pre-Rough Approximation Space with Applications in Decision Making},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {132},
YEAR = {2022},
NUMBER = {3},
PAGES = {865--879},
URL = {http://www.techscience.com/CMES/v132n3/48677},
ISSN = {1526-1506},
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.},
DOI = {10.32604/cmes.2022.020066}
}