通过贝塞尔函数预测欧洲国家Covid-19感染的理论:过去和现在

H. Nieto-Chaupis
{"title":"通过贝塞尔函数预测欧洲国家Covid-19感染的理论:过去和现在","authors":"H. Nieto-Chaupis","doi":"10.1109/TransAI51903.2021.00021","DOIUrl":null,"url":null,"abstract":"The data of infections by Covid-19 is modeled through the integer-order Bessel functions that have been parametrized in according to the morphology of data. In particular, the modeling is focused on official data belonging to UK, Germany, Italy and Netherlands. The free parameters of model have been coherently linked to data. Interestingly, it was seen that a \"silent period\" with the lowest cases of infections play a relevant role for new pandemics as well as the apparition of new strains, such as the most recent \"delta-variant\".","PeriodicalId":426766,"journal":{"name":"2021 Third International Conference on Transdisciplinary AI (TransAI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Predictive Theory of Covid-19 Infections at European Countries Through Bessel Functions: Past and Present\",\"authors\":\"H. Nieto-Chaupis\",\"doi\":\"10.1109/TransAI51903.2021.00021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The data of infections by Covid-19 is modeled through the integer-order Bessel functions that have been parametrized in according to the morphology of data. In particular, the modeling is focused on official data belonging to UK, Germany, Italy and Netherlands. The free parameters of model have been coherently linked to data. Interestingly, it was seen that a \\\"silent period\\\" with the lowest cases of infections play a relevant role for new pandemics as well as the apparition of new strains, such as the most recent \\\"delta-variant\\\".\",\"PeriodicalId\":426766,\"journal\":{\"name\":\"2021 Third International Conference on Transdisciplinary AI (TransAI)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Third International Conference on Transdisciplinary AI (TransAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TransAI51903.2021.00021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Third International Conference on Transdisciplinary AI (TransAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TransAI51903.2021.00021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

通过根据数据形态参数化的整阶贝塞尔函数对Covid-19感染数据进行建模。该模型特别关注英国、德国、意大利和荷兰的官方数据。模型的自由参数与数据进行了相干关联。有趣的是,据认为,感染病例最低的"沉默期"对新的流行病以及新菌株的出现,如最近的"德尔塔变种",发挥了相关作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Theory of Covid-19 Infections at European Countries Through Bessel Functions: Past and Present
The data of infections by Covid-19 is modeled through the integer-order Bessel functions that have been parametrized in according to the morphology of data. In particular, the modeling is focused on official data belonging to UK, Germany, Italy and Netherlands. The free parameters of model have been coherently linked to data. Interestingly, it was seen that a "silent period" with the lowest cases of infections play a relevant role for new pandemics as well as the apparition of new strains, such as the most recent "delta-variant".
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:604180095
Book学术官方微信