Multi-information Collaborative Model of Urban Public Health Emergency Management Based on Bayesian Algorithm

Lijun Sun, Dan Li
{"title":"Multi-information Collaborative Model of Urban Public Health Emergency Management Based on Bayesian Algorithm","authors":"Lijun Sun, Dan Li","doi":"10.1109/ICDCECE57866.2023.10151274","DOIUrl":null,"url":null,"abstract":"Urban public health emergency management is a series of measures taken by the government to maintain and promote social stability and development. After the occurrence of an emergency, relevant systems are established and improved to ensure public safety. This paper first introduces the background and significance of the research, as well as the mature theoretical basis for the construction of urban government’s response to sudden disasters and emergency response capacity at home and abroad. On this basis, a dynamic response model of urban public health based on Bayesian network is proposed for analysis and research. The final test results show that the urban emergency rescue system based on Bayesian algorithm has better effect than the traditional prediction method relying on a single node, with rapid operation time and small error in information synchronization time. Under this application mode, a whole composed of multiple nodes is established to simulate the management and control of various government departments when an emergency occurs.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCECE57866.2023.10151274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Urban public health emergency management is a series of measures taken by the government to maintain and promote social stability and development. After the occurrence of an emergency, relevant systems are established and improved to ensure public safety. This paper first introduces the background and significance of the research, as well as the mature theoretical basis for the construction of urban government’s response to sudden disasters and emergency response capacity at home and abroad. On this basis, a dynamic response model of urban public health based on Bayesian network is proposed for analysis and research. The final test results show that the urban emergency rescue system based on Bayesian algorithm has better effect than the traditional prediction method relying on a single node, with rapid operation time and small error in information synchronization time. Under this application mode, a whole composed of multiple nodes is established to simulate the management and control of various government departments when an emergency occurs.
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
基于贝叶斯算法的城市公共卫生应急管理多信息协同模型
城市公共卫生应急管理是政府为维护和促进社会稳定与发展而采取的一系列措施。在突发事件发生后,建立和完善相关制度,保障公共安全。本文首先介绍了研究的背景和意义,以及国内外城市政府应对突发灾害和应急响应能力建设的成熟理论基础。在此基础上,提出了基于贝叶斯网络的城市公共卫生动态响应模型进行分析研究。最终的试验结果表明,基于贝叶斯算法的城市应急救援系统比传统的依赖单个节点的预测方法效果更好,运行时间快,信息同步时间误差小。在该应用模式下,建立一个由多个节点组成的整体,模拟突发事件发生时政府各部门的管控情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Smart Development of Maximum Distance Rendezvous Point Model For Commercial Scheduling of Complex Networks Detecting Image Forgeries: A Key-Point Based Approach Students Performance Monitoring and Customized Recommendation Prediction in Learning Education using Deep Learning A System for Detecting Automated Parking Slots Using Deep Learning Carbon Productivity Improvement for Manufacturing Based on AI
×
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