Pokkuluri Kiran Sree1* and SSSN Usha Devi N2
1Professor, Department of CSE, Shri Vishnu Engineering College for Women, Bhimavaram, India
2Assistant Professor, Department of CSE, University College of Engineering-Kakinada, JNTU-K, India
*Corresponding Author: Pokkuluri Kiran Sree, Professor, Department of CSE, Shri Vishnu Engineering College for Women, Bhimavaram, India.
Received: July 24, 2020; Published:August 19, 2020
COVID-19 recovery prediction is pronounced as one of the toughest problems that the world is facing now. The variations of deaths and recovery rates are changing drastically. There is an increase in the recovery rate and a decrease in the relative death rate with time. Very few researchers have focused on the recovery rate. The datasets are collected from Kaggle and processed with Non-Linear Cellular Automata to predict the recovery rate in India. The developed classifier is compared with the existing standard literature like Support Vector Machine(SVM), Random Forest(RF) and K-Means(K-ME) algorithm. Our classifier reports an accuracy of 89.94%, which was considerably better at this moment.
Keywords: COVID-19; Cellular Automata; Recovery Rate
Citation: Pokkuluri Kiran Sree and SSSN Usha Devi N. “COVID-19 Recovery Rate Prediction in India with Cellular Automata". Acta Scientific Computer Sciences 2.9 (2020): 18-20.
Copyright: © 2020 Pokkuluri Kiran Sree and SSSN Usha Devi N. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.