{"title":"Fire Risk Assessment in Universities Based on Fault Tree Analysis and\n Bayesian Network","authors":"A. Yang, Beibei Sun","doi":"10.54941/ahfe1002846","DOIUrl":null,"url":null,"abstract":"In order to scientifically and accurately analyze the fire hazards\n existing in colleges and universities, and put forward feasible suggestions\n for eliminating hidden dangers, a fire risk assessment method based on Fault\n tree analysis and Bayesian network is proposed.Firstly, the Fault tree of\n the large loss caused by the fire in the university premises is constructed,\n and then the Fault tree is transformed into a Bayesian network model. In\n this method, the failure risk of the fire protection system can be obtained\n by forward reasoning according to the probability of the basic events in the\n fire, and finally, the reliability of the fire protection system of the\n whole university is analyzed.At the same time, combined with the reverse\n diagnosis and reasoning technology of Bayesian network, according to the\n known or assumed state of leaf nodes, the posterior probability and\n probability importance degree of each root node can be reversed to check the\n weak links in the fire protection system. In the conclusion, suggestions and\n rectification strategies are put forward for the fire protection system in\n colleges and universities.This paper proposes a method that combines fault\n tree analysis with Bayesian network and applies it to fire risk assessment\n in colleges and universities. Based on the fire protection big data, the\n software Genie3.0 is used to construct a Bayesian network model of fire risk\n in universities, and an example analysis of fire risk assessment is carried\n out by taking a university in Nanjing as an example, which not only analyzes\n the reliability of the entire system, but also It also uses the\n bidirectional reasoning ability of Bayesian network to analyze the weak link\n performance of the system, which improves the model's description ability\n and inference computing ability. It is proved that the FTA-BN method has\n application potential in the field of fire risk assessment.","PeriodicalId":269162,"journal":{"name":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1002846","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

In order to scientifically and accurately analyze the fire hazards existing in colleges and universities, and put forward feasible suggestions for eliminating hidden dangers, a fire risk assessment method based on Fault tree analysis and Bayesian network is proposed.Firstly, the Fault tree of the large loss caused by the fire in the university premises is constructed, and then the Fault tree is transformed into a Bayesian network model. In this method, the failure risk of the fire protection system can be obtained by forward reasoning according to the probability of the basic events in the fire, and finally, the reliability of the fire protection system of the whole university is analyzed.At the same time, combined with the reverse diagnosis and reasoning technology of Bayesian network, according to the known or assumed state of leaf nodes, the posterior probability and probability importance degree of each root node can be reversed to check the weak links in the fire protection system. In the conclusion, suggestions and rectification strategies are put forward for the fire protection system in colleges and universities.This paper proposes a method that combines fault tree analysis with Bayesian network and applies it to fire risk assessment in colleges and universities. Based on the fire protection big data, the software Genie3.0 is used to construct a Bayesian network model of fire risk in universities, and an example analysis of fire risk assessment is carried out by taking a university in Nanjing as an example, which not only analyzes the reliability of the entire system, but also It also uses the bidirectional reasoning ability of Bayesian network to analyze the weak link performance of the system, which improves the model's description ability and inference computing ability. It is proved that the FTA-BN method has application potential in the field of fire risk assessment.
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
基于故障树分析和贝叶斯网络的高校火灾风险评估
为了科学准确地分析高校存在的火灾隐患,提出消除隐患的可行建议,提出了一种基于故障树分析和贝叶斯网络的火灾风险评估方法。首先构建了高校校舍火灾造成重大损失的故障树,然后将故障树转化为贝叶斯网络模型。该方法根据火灾中基本事件的概率,通过前向推理得到消防系统的失效风险,最后对整个高校消防系统的可靠性进行分析。同时,结合贝叶斯网络的反向诊断和推理技术,根据叶节点的已知状态或假设状态,反演各根节点的后验概率和概率重要度,检查消防系统中的薄弱环节。在结论部分,对高校消防系统提出了建议和整改策略。本文提出了一种将故障树分析与贝叶斯网络相结合的方法,并将其应用于高校火灾风险评估。基于消防大数据,利用Genie3.0软件构建高校火灾风险贝叶斯网络模型,并以南京某高校为例进行火灾风险评估实例分析,不仅分析了整个系统的可靠性,还利用贝叶斯网络的双向推理能力分析了系统的薄弱环节性能。提高了模型的描述能力和推理计算能力。证明了该方法在火灾风险评估领域具有应用潜力。
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
Interaction between humans and autonomous systems: Human facing explanatory interface for an urban autonomous passenger ferry Sensor based ergonomic cushion for posture detection and correction User-centred generation of early-concept Mobility-as-a-Service interface designs aimed at promoting greener travel Exploring remote operation of heavy vehicles – findings from a simulator study An Intelligent Retrieval Method of Building Fire Safety Knowledge Based on Knowledge Graph
×
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