一种新的智能建筑火灾风险分类方法*

Weilin Wu, Na Wang, Yixiang Chen
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引用次数: 0

摘要

为了对智能建筑的火灾风险进行评估,建立了可信赖分类模型,为城市智能消防建设下的智能建筑火灾风险分类评估提供了模型支持。该模型将贝叶斯网络(BN)与软件可信计算理论和方法相结合,从火情、建筑、环境和人员四个维度设计度量元素和属性,对火灾风险进行评估;用BN计算火灾属性的风险值;然后,利用可信评估模型将火灾风险属性值融合为火灾风险可信值;本文构建了智能建筑火灾风险可信分类模型,并根据火灾风险的可信值和属性值将火灾风险分为五个等级。以上海静安11.15火灾为例,结果表明本文所提供的方法可以进行火灾风险评估和分类。
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A Novel Intelligent-Building-Fire-Risk Classification Method*
In order to assess the fire risk of the intelligent buildings, a trustworthy classification model was developed, which provides model supporting for the classification assessment of fire risk in intelligent buildings under the urban intelligent firefight construction. The model integrates Bayesian Network (BN) and software trustworthy computing theory and method, designs metric elements and attributes to assess fire risk from four dimensions of fire situation, building, environment and personnel; BN is used to calculate the risk value of fire attributes; Then, the fire risk attribute value is fused into the fire risk trustworthy value by using the trustworthy assessment model; This paper constructs a trustworthy classification model for intelligent building fire risk, and classifies the fire risk into five ranks according to the trustworthy value and attribute value. Taking the Shanghai Jing'an 11.15 fire as an example case, the result shows that the method provided in this paper can perform fire risk assessment and classification.
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Parameter Sensitive Pointer Analysis for Java Optimizing Parallel Java Streams Parameterized Design and Formal Verification of Multi-ported Memory Extension-Compression Learning: A deep learning code search method that simulates reading habits Proceedings 2022 26th International Conference on Engineering of Complex Computer Systems [Title page iii]
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