Time Series Facebook Prophet Model and Python for COVID-19 Outbreak Prediction

作     者：Mashael Khayyat Kaouther Laabidi Nada Almalki Maysoon Al-zahrani 

作者机构：Department of Information Systems and TechnologyCollage of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia Department of Computer and Network EngineeringCollage of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia and University of TunisElmanarTunisia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2021年第67卷第6期

页      面：3781-3793页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：COVID-19 time series analysis prediction face book prophet model python 

摘      要：COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect *** the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and *** researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic ***,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting *** research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various ***,we proposed a prediction and analysis model to predict COVID-19 in Saudi *** time series dependent face book prophet model is used to t the data and provide future *** study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or *** found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 *** contrast,the proposed model of death cases has a high ability to forecast the COVID-19 ***,obtaining more data could empower the model for further validation.