Title: Predicting the possibility of COVID-19 infection using fuzzy logic system

Authors: Shadab Hafiz Choudhury; Azmary Jannat Aurin; Tanbin Akter Mitaly; Rashedur M. Rahman

Addresses: Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh ' Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh ' Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh ' Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh

Abstract: Diagnosing COVID-19 in a fast and efficient manner is an ongoing problem. Currently, the methods of detection involve physical tests. Physical tests have the disadvantage that they require either test kits or medical equipment. This paper outlines the design of a type-2 fuzzy logic system that can help provide a preliminary diagnosis by computing the possibility that a patient is suffering from COVID-19 based on their external symptoms. It uses input information that can be gleaned without need for medical procedures. Both statistical data and the knowledge base were garnered from publicly available databases and datasets. The fuzzy logic system implemented here is functional, but it is fairly inaccurate and illustrates that more information, both symptomatic and epidemiological is needed, to predict COVID-19 infections through an expert system.

Keywords: iterative type-2 fuzzy logic system; Mamdani fuzzy inference; novel coronavirus; COVID-19.

DOI: 10.1504/IJIIDS.2021.116465

International Journal of Intelligent Information and Database Systems, 2021 Vol.14 No.3, pp.239 - 256

Received: 29 Jun 2020
Accepted: 17 Sep 2020
Published online: 26 Jul 2021 *

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