|本期目录/Table of Contents|

[1]颜峻,孟燕华,左哲.基于Bayesian网络的建筑火灾疏散条件安全性评估方法*[J].中国安全生产科学技术,2020,16(12):116-121.[doi:10.11731/j.issn.1673-193x.2020.12.019]
　YAN Jun,MENG Yanhua,ZUO Zhe.Study on assessment method for safety of evacuation conditions in building fire based on Bayesian network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(12):116-121.[doi:10.11731/j.issn.1673-193x.2020.12.019]
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基于Bayesian网络的建筑火灾疏散条件安全性评估方法*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
16
期数:
2020年12期
页码:
116-121
栏目:
职业安全卫生管理与技术
出版日期:
2020-12-31

文章信息/Info

Title:
Study on assessment method for safety of evacuation conditions in building fire based on Bayesian network
文章编号:
1673-193X(2020)-12-0116-06
作者:
颜峻1; 孟燕华1; 左哲2
（1.中国劳动关系学院 安全与职业卫生工程研究所，北京 100048；
2.中国安全生产科学研究院，北京 100012）
Author(s):
YAN Jun;  MENG Yanhua;  ZUO Zhe
(1.Institute of Safety and Occupational Hygiene Engineering,China Institute of Industrial Relations,Beijing 100048,China;
2.China Academy of Safety Science and Technology,Beijing 100012,China)
关键词:
火灾; 疏散条件; 安全性评估; Bayesian网络
Keywords:
fire;  evacuation condition;  safety assessment;  Bayesian network
分类号:
X932
DOI:
10.11731/j.issn.1673-193x.2020.12.019
文献标志码:
A
摘要:
为了对建筑火灾疏散条件安全性进行评估，基于Bayesian网络对疏散条件重要构成要素及评估方法逻辑推理过程进行研究探讨。结果表明：评估网络结构、根节点、中间节点及目标节点之间存在因果关联关系；研究得出根节点先验概率与量化节点条件概率表设定方法；Bayesian网络将风险评估与人工智能分析方法相结合，实现对建筑火灾疏散条件的安全性评估，并可用于识别高风险建筑。
Abstract:
In order to assess the safety of evacuation conditions in the building fire,the important components of evacuation conditions were studied,and the logical reasoning process of the assessment method was discussed.A comprehensive assessment method for the safety of evacuation conditions based on the Bayesian network was constructed,and the causal association relationship between the assessment network structure,root nodes,intermediate nodes and target nodes was illustrated,as well as the setting method for the conditional probability table of the prior probability of root nodes correlated with the quantized nodes.The results showed that the assessment on the safety of evacuation conditions was an important link in the risk assessment of building fire,there were many influencing factors,and there exited the causal association between them.The Bayesian network could combine the risk assessment with the artificial intelligence analysis method,realize the assessment on the safety of evacuation conditions in the building fire,and identify the high risk buildings.

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备注/Memo

备注/Memo:
收稿日期： 2020-11-30
* 基金项目： 中国劳动关系学院2020年校级科研基金项目(20XYJ021)
作者简介： 颜俊,博士,副教授,主要研究方向为公共安全、建筑防火技术、火灾风险评估及智慧消防。
通信作者： 左哲，硕士，教授级高级工程师，主要研究方向为安全发展示范城市建设、火灾安全科学。
更新日期/Last Update: 2021-01-08