Fuzzy Rule-Based System for Predicting Daily Case in COVID-19 Outbreak
Pınar Cihan
Abstract
The Covid-19 outbreak appeared in Wuhan in December 2019 and spread rapidly all over the world. The Covid-19 disease does not yet have a clinically proven vaccine and drug for treatment. The most important physical factors in reducing the spread of the epidemic are washing hands, reducing social distance and using a mask. Today in addition to clinical studies, computer-aided studies are also widely carried out for Covid-19 outbreak. Artificial intelligence methods are successfully applied in epidemic studies. In this study, fuzzy rule basing system (FRGS) used to predict the number of Covid-19 daily cases. As a result of the study, the number of daily cases was successfully estimated with FRGS (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.96, MAE = 186 and RMSE = 254).