基于机器学习方法的2019冠状病毒疫情数据分析——以印度为例

Ramjeet Singh Yadav
{"title":"基于机器学习方法的2019冠状病毒疫情数据分析——以印度为例","authors":"Ramjeet Singh Yadav","doi":"10.1007/s41870-020-00484-y","DOIUrl":null,"url":null,"abstract":"<p><p>At this time, COVID-2019 is spreading its foot in the form of a huge epidemic for the world. This epidemic is spreading its foot very fast in India too. One of the World Health Organization states that COVID-2019 is a serious disease that spreads from one person to another at very fast speed through contact routes and respiratory drops. On this day, India and the world should rise to an effective step to analyze this disease and eliminate the effects of this epidemic. In this paper presented, the growing database of COVID-2019 has been analyzed from March 1, 2020, to April 11, 2020, and the next one is predicted for the number of patients suffering from the rising COVID-2019. Different regression analysis models have been utilized for data analysis of COVID-2019 of India based on data stored by Kaggle in between 1 March 2020 to 11 April 2020. In this study, we have been utilized six regression analysis based models namely quadratic, third degree, fourth degree, fifth degree, sixth degree, and exponential polynomial respectively for the COVID-2019 dataset. We have calculated the root mean square of these six regression analysis models. In these six models, the root mean square error of sixth degree polynomial is very less in compared other like quadratic, third degree, fourth degree, fifth degree, and exponential polynomial. Therefore the sixth degree polynomial regression model is very good models for forecasting the next 6 days for COVID-2019 data analysis in India. In this study, we have found that the sixth degree polynomial regression models will help Indian doctors and the Government in preparing their plans in the next 7 days. Based on further regression analysis study, this model can be tuned for forecasting over long term intervals.</p>","PeriodicalId":73455,"journal":{"name":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41870-020-00484-y","citationCount":"1","resultStr":"{\"title\":\"Data analysis of COVID-2019 epidemic using machine learning methods: a case study of India.\",\"authors\":\"Ramjeet Singh Yadav\",\"doi\":\"10.1007/s41870-020-00484-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>At this time, COVID-2019 is spreading its foot in the form of a huge epidemic for the world. This epidemic is spreading its foot very fast in India too. One of the World Health Organization states that COVID-2019 is a serious disease that spreads from one person to another at very fast speed through contact routes and respiratory drops. On this day, India and the world should rise to an effective step to analyze this disease and eliminate the effects of this epidemic. In this paper presented, the growing database of COVID-2019 has been analyzed from March 1, 2020, to April 11, 2020, and the next one is predicted for the number of patients suffering from the rising COVID-2019. Different regression analysis models have been utilized for data analysis of COVID-2019 of India based on data stored by Kaggle in between 1 March 2020 to 11 April 2020. In this study, we have been utilized six regression analysis based models namely quadratic, third degree, fourth degree, fifth degree, sixth degree, and exponential polynomial respectively for the COVID-2019 dataset. We have calculated the root mean square of these six regression analysis models. In these six models, the root mean square error of sixth degree polynomial is very less in compared other like quadratic, third degree, fourth degree, fifth degree, and exponential polynomial. Therefore the sixth degree polynomial regression model is very good models for forecasting the next 6 days for COVID-2019 data analysis in India. In this study, we have found that the sixth degree polynomial regression models will help Indian doctors and the Government in preparing their plans in the next 7 days. Based on further regression analysis study, this model can be tuned for forecasting over long term intervals.</p>\",\"PeriodicalId\":73455,\"journal\":{\"name\":\"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s41870-020-00484-y\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41870-020-00484-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/5/26 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41870-020-00484-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/5/26 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

此时此刻,2019冠状病毒病正在以一场巨大的流行病的形式向全世界蔓延。这种流行病在印度也蔓延得非常快。世界卫生组织表示,covid - 19是一种严重的疾病,通过接触途径和呼吸滴剂以非常快的速度在人与人之间传播。在这一天,印度和世界应该采取有效步骤,分析这一疾病并消除这一流行病的影响。本文分析了2020年3月1日至2020年4月11日的COVID-2019增长数据库,并预测了下一个COVID-2019上升的患者数量。根据Kaggle存储的2020年3月1日至2020年4月11日期间的数据,利用不同的回归分析模型对印度2019年covid - 19进行了数据分析。在本研究中,我们对COVID-2019数据集分别使用了二次、三次、四次、五次、六次和指数多项式六种基于回归分析的模型。我们计算了这六个回归分析模型的均方根。在这六种模型中,与二次多项式、三次多项式、四次多项式、五次多项式和指数多项式相比,六次多项式的均方根误差很小。因此,六次多项式回归模型是预测印度未来6天COVID-2019数据分析的非常好的模型。在这项研究中,我们发现六次多项式回归模型将有助于印度医生和政府在未来7天内准备他们的计划。基于进一步的回归分析研究,该模型可以进行长期预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Data analysis of COVID-2019 epidemic using machine learning methods: a case study of India.

Data analysis of COVID-2019 epidemic using machine learning methods: a case study of India.

Data analysis of COVID-2019 epidemic using machine learning methods: a case study of India.

Data analysis of COVID-2019 epidemic using machine learning methods: a case study of India.

At this time, COVID-2019 is spreading its foot in the form of a huge epidemic for the world. This epidemic is spreading its foot very fast in India too. One of the World Health Organization states that COVID-2019 is a serious disease that spreads from one person to another at very fast speed through contact routes and respiratory drops. On this day, India and the world should rise to an effective step to analyze this disease and eliminate the effects of this epidemic. In this paper presented, the growing database of COVID-2019 has been analyzed from March 1, 2020, to April 11, 2020, and the next one is predicted for the number of patients suffering from the rising COVID-2019. Different regression analysis models have been utilized for data analysis of COVID-2019 of India based on data stored by Kaggle in between 1 March 2020 to 11 April 2020. In this study, we have been utilized six regression analysis based models namely quadratic, third degree, fourth degree, fifth degree, sixth degree, and exponential polynomial respectively for the COVID-2019 dataset. We have calculated the root mean square of these six regression analysis models. In these six models, the root mean square error of sixth degree polynomial is very less in compared other like quadratic, third degree, fourth degree, fifth degree, and exponential polynomial. Therefore the sixth degree polynomial regression model is very good models for forecasting the next 6 days for COVID-2019 data analysis in India. In this study, we have found that the sixth degree polynomial regression models will help Indian doctors and the Government in preparing their plans in the next 7 days. Based on further regression analysis study, this model can be tuned for forecasting over long term intervals.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信