{"title":"基于故障树分析和贝叶斯网络的高校火灾风险评估","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":"{\"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}","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}
Fire Risk Assessment in Universities Based on Fault Tree Analysis and
Bayesian Network
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.