利用贝叶斯方法预测新型冠状病毒肺炎疫情
首发时间:2020-03-26
摘要:近年来贝叶斯机器学习方法在各行各业中都得到了很好地应用。作者使用该方法研究了国际上正在肆虐的新型冠状病毒肺炎疫情。结果发现利用贝叶斯机器学习方法能够实现对疫情演化曲线的预测,不仅能给出模型参数的中值,也可以估算其误差大小。论文给出了对韩国、意大利和伊朗疫情的预测结果。
关键词: 流行病与卫生统计学,新型冠状病毒肺炎,疾病传播,贝叶斯机器学习
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Predict COVID-19 epidemic with Bayesian method
Abstract:Bayesian machine learning has been successfully applied in many field recent years. The method is used to study of the ongoing COVID-19 in the world. The result shows that the evolution curve of the epidemic can be predicted with Bayesian machine learning method, not only the central values of the model parameters, but also their error bars. The evolution curves of the cumulative confirmed cases in Korea, Italy and Iran are presented in the present work.
Keywords: Epidemiology and health statistics, COVID-19, disease transmission,Bayesian machine learning
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