2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 5 , Issue 2 , PP: 97-109, 2021 | Cite this article as | XML | Html | PDF | Full Length Article
Abedallah Zaid Abualkishik 1 *
Doi: https://doi.org/10.54216/JISIoT.050205
Coronavirus Illness 2019 (COVID-19), a rare disease carried by a coronavirus known as a novel coronavirus, is now posing a danger to the whole planet. Despite the rising number of cases, there is no commercially available vaccination for COVID-19. The moderate symptoms of COVID-19 illness, on the other hand, may be treated with a variety of antiviral treatments. Even yet, selecting the optimum antiviral medication to manage the moderate symptom of COVID-19 is a difficult and ambiguous option. Selecting a drug might be challenging. Fuzzy collaborative intelligence (FCI) was presented in this research as a solution to solve the difficulty of evaluating the appropriateness of a drug selection. In the FCI method, the fuzzy inverse of column sum, partial consensus fuzzy intersection, and fuzzy procedure for order preference by similarity to the ideal solution. To show the practicality and usefulness of the created approach in real-world applications, a case study of medication choice for COVID-19 illness is being investigated.
Fuzzy Collaborative Intelligence , TOPSIS , Drug , COVID-19
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