Analyzing and Predicting the Deaths and Cases of Covid-19 in Different Countries Using Fuzzy K Means Algorithm and Exponential Method

Abstract

Covid-19 disease, since it first appearance in the Chinese city of Wuhan, has led to many infections and deaths, not only in China, but also in most countries of the world. The most prominent symptoms of this disease are headache, fever, strong cough, and perhaps the strongest of it is difficulty breathing in the event that the virus reaches the lung, which leads to death in many cases if the patient's condition is late, or he does not have strong immunity. The purpose of this study is to use Fuzzy k Means (FKM) and predictive algorithm representing in Simple Exponential Smoothing Method (SESM) to evaluate confirmed cases and deaths in different countries. This study's findings show that the FKM approach can evaluate data and produce reliable results, in addition to the SESM can give good prediction. According to this study, machine learning technologies and predicting methodologies achieved good results when used together.