改进EKF预测Covid-19的3个移动限制(研究案例:印度尼西亚)

H. N. Fadhilah, Amalia Nur Alifah, Mohammad Hamim Zajuli Al Faroby, D. K. Arif
{"title":"改进EKF预测Covid-19的3个移动限制(研究案例:印度尼西亚)","authors":"H. N. Fadhilah, Amalia Nur Alifah, Mohammad Hamim Zajuli Al Faroby, D. K. Arif","doi":"10.1063/5.0117110","DOIUrl":null,"url":null,"abstract":"In this paper, the spread of the Covid-19 in.Indonesia is described by the SIRD epidemiological mathematical model. The mathematical model used in this paper is Susceptible, Infected, Recovered, Death (SIRD). The modified extended Kalman filter algorithm is applied to predict the spread of Covid-19 in.the future. We modified the algorithm by generating real data based on the previous estimation results. The real data generated from the generation is used at the correction stage to obtain prediction results in a fairly long period. Simulations were carried out with three types of mobility restrictions, namely mobility 100%, mobility 75%, and mobility 50%. Based on the simulation results, it can be concluded that mobility restrictions in Indonesia, which starts on September 4, 2020, can reduce the number of infected and death individuals and can increase the number of individuals who recover from Covid-19. © 2022 Author(s).","PeriodicalId":56955,"journal":{"name":"应用数学与计算数学学报","volume":"138 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modified EKF for Covid-19 prediction with 3 mobility restrictions (Study Case: Indonesia)\",\"authors\":\"H. N. Fadhilah, Amalia Nur Alifah, Mohammad Hamim Zajuli Al Faroby, D. K. Arif\",\"doi\":\"10.1063/5.0117110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the spread of the Covid-19 in.Indonesia is described by the SIRD epidemiological mathematical model. The mathematical model used in this paper is Susceptible, Infected, Recovered, Death (SIRD). The modified extended Kalman filter algorithm is applied to predict the spread of Covid-19 in.the future. We modified the algorithm by generating real data based on the previous estimation results. The real data generated from the generation is used at the correction stage to obtain prediction results in a fairly long period. Simulations were carried out with three types of mobility restrictions, namely mobility 100%, mobility 75%, and mobility 50%. Based on the simulation results, it can be concluded that mobility restrictions in Indonesia, which starts on September 4, 2020, can reduce the number of infected and death individuals and can increase the number of individuals who recover from Covid-19. © 2022 Author(s).\",\"PeriodicalId\":56955,\"journal\":{\"name\":\"应用数学与计算数学学报\",\"volume\":\"138 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"应用数学与计算数学学报\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.1063/5.0117110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"应用数学与计算数学学报","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1063/5.0117110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了新型冠状病毒在中国的传播情况。印度尼西亚是由SIRD流行病学数学模型描述的。本文使用的数学模型是易感、感染、恢复、死亡(SIRD)。应用改进的扩展卡尔曼滤波算法预测新冠肺炎在北京的传播。未来。我们通过在之前估计结果的基础上生成真实数据来改进算法。在校正阶段使用生成的真实数据,以获得相当长时间内的预测结果。模拟采用100%、75%和50%三种不同的移动性限制。根据模拟结果,可以得出结论,从2020年9月4日开始,印度尼西亚的流动限制可以减少感染和死亡人数,并可以增加从Covid-19中康复的人数。©2022作者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Modified EKF for Covid-19 prediction with 3 mobility restrictions (Study Case: Indonesia)
In this paper, the spread of the Covid-19 in.Indonesia is described by the SIRD epidemiological mathematical model. The mathematical model used in this paper is Susceptible, Infected, Recovered, Death (SIRD). The modified extended Kalman filter algorithm is applied to predict the spread of Covid-19 in.the future. We modified the algorithm by generating real data based on the previous estimation results. The real data generated from the generation is used at the correction stage to obtain prediction results in a fairly long period. Simulations were carried out with three types of mobility restrictions, namely mobility 100%, mobility 75%, and mobility 50%. Based on the simulation results, it can be concluded that mobility restrictions in Indonesia, which starts on September 4, 2020, can reduce the number of infected and death individuals and can increase the number of individuals who recover from Covid-19. © 2022 Author(s).
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
912
期刊最新文献
The reduced GTH-gene expression caused by mHtt on Sp1 will ultimately result in cell death Review of NIR spectroscopy applications in medical field A mathematical model of premium fund management in sharia insurance under modified-mudharabah scheme The modeling of frequency-magnitude of earthquakes in Indonesia using Poisson regression Big data prototype development in Hadoop ecosystem using HDFS and mapreduce as the parallel computation model - Case study: Samples of intelligent transportation of Surabaya City
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1