文章基本信息

标题：The prediction of coronavirus disease 2019 outbreak on Bangladesh perspective using machine learning: a comparative study
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作者：Maqsudur Rahman ; Md.Tofael Ahmed ; Shafayet Nur 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：4
页码：4276-4287
DOI：10.11591/ijece.v12i4.pp4276-4287
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Coronavirus disease 2019 (COVID-19) has made a huge pandemic situation in many countries of the world including Bangladesh. If the increase rate of this threat can be forecasted, immediate measures can be taken. This study is an effort to forecast the threat of present pandemic situation using machine learning (ML) forecasting models. Forecasting was done in three categories in the next 30 days range. In our study, multiple linear regression performed best among the other algorithms in all categories with R2 score of 99% for first two categories and 94% for the third category. Ridge regression performed great for the first two categories with R2 scores of 99% each but performed poorly for the third category with R2 score of 43%. Lasso regression performed reasonably well with R2 scores of 97%, 99% and 75% for the three categories. We also used Facebook Prophet to predict 30 days beyond our train data which gave us healthy R2 scores of 92% and 83% for the first two categories but performed poorly for the third category with R2 score of 34%. Also, all the models’ performances were evaluated with a 40-day prediction interval in which multiple linear regression outperformed other algorithms.
关键词：Coronavirus disease 2019;Facebook Prophet;Lasso regression;Multiple linear regression;Ridge regression