COVID-19 Prediction and analysis using Neural Network and Pearson Correlation

Suyog S. Sawant, Aaryan Agrawal, Kavita Tewari
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引用次数: 0

Abstract

In the present study, a neural network-based predictive model has been used to predict the trend of the second wave of COVID-19 in a few countries, namely the US, UK, Brazil, South Africa, and India. The Neural Network model was trained for the rise of first-wave and refined predicting and comparing the predictions with the observed trends of the second waves in these countries. As the US has seen a clear-cut arrival of third-wave, the methodused was a neural network tool on Matlab software to predict the covid-19 wave pattern and later used to have a prediction of third-wave in India. Pearson correlation coefficient between the covid first wave and second wave for five countries was also computed and results were rationalized in terms of the extent of population vaccinated in these countries.
基于神经网络和Pearson相关的COVID-19预测与分析
本研究利用基于神经网络的预测模型,对美国、英国、巴西、南非、印度等国家的第二波疫情趋势进行了预测。神经网络模型针对第一波浪潮的兴起进行了训练,并对这些国家的第二波浪潮进行了精确的预测,并将预测结果与观察到的趋势进行了比较。由于美国已经出现了明确的第三波到来,因此使用的方法是Matlab软件上的神经网络工具来预测covid-19的波浪模式,后来用于预测印度的第三波。还计算了五个国家的第一波和第二波之间的Pearson相关系数,并根据这些国家接种疫苗的人口范围对结果进行了合理化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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