使用机器学习方法预测新冠肺炎病例、死亡和康复

M. Lounis, F. Khan
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引用次数: 5

摘要

在所介绍的工作中,我们使用2020年2月25日至2021年4月26日的数据,应用三种机器学习技术预测和预测阿尔及利亚未来六个月的新冠肺炎病例、死亡和康复人数。这些模型由高斯过程回归(GPR)、支持向量机(SVM)和决策树(DT)表示。绘图结果和参数评估表明,高斯过程回归(GPR)具有最好的性能。该模型的预测显示,未来几个月,阿尔及利亚的病例数、死亡人数和康复人数将增加,8月份将达到峰值,此后曲线将趋于下降。
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Predicting COVID-19 cases, deaths and recoveries using machine learning methods
In the presented work we applied three machine learning techniques to forecast and predict COVID-19 cases, deaths ad recoveries numbers in Algeria for the next six months using data from February 25th, 2020 to April 26th , 2021. These models are represented by the Gaussian process regression (GPR), the support vector machine (SVM) and the decision tree (DT). The plotting results and parameters evaluation pointed out that the Gaussian Process Regression (GPR) has the best performance. Prediction with this model showed that the number of cases, deaths and recoveries will increase in the next months Algeria recording a peak in the month of August and the curve will tend to decrease later.
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