Cotton storage fire develops rapidly, and it has high probability of being out of control and causing huge economic loss. In order to carry out a quantitative risk assessment of cotton storage fire accidents, a dynamic risk assessment model of cotton storage fire is established by means of data analysis, fuzzy comprehensive evaluation (FCE), cases study and expert opinions based on Bayesian network (BN). The model includes three sections (fire causes section, fire discoverer section, fire control section) and one mainline, with 22 nodes, and gives accident risk in the form of economic loss. Risk can be renewed quickly by giving new evidence to model nodes of BN. The application of FCE provides a feasible solution to solve the data deficiency problem in databases, experiment results and experience in model construction. Sensitivity analysis result shows firefighters participation, timely control of fire, firefighting systems and workers are important to put out the fire. A case study shows that the loss of a fire accident happened in an open storage yard is more serious than the loss of a similar fire accident happened in warehouse. This model provides support for cotton storage fire risk management and decision‐making in an emergency fire accident.

中文翻译：

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基于模糊综合评价和贝叶斯网络的棉花储藏库火灾风险评估

棉花储存火灾发展迅速，极有可能失控并造成巨大的经济损失。为了对棉花储存火灾事故进行定量风险评估，建立了基于数据分析，模糊综合评价（FCE），案例研究和专家意见的基于贝叶斯网络的棉花储存火灾动态风险评估模型。 ）。该模型包括三个部分（火灾原因部分，火灾发现者部分，消防控制部分）和一个主干，具有22个节点，并以经济损失的形式给出事故风险。通过为BN的模型节点提供新证据，可以快速更新风险。FCE的应用为解决数据库中的数据不足问题，实验结果和模型构建经验提供了可行的解决方案。敏感性分析结果表明，消防员的参与，及时控制火势，消防系统和工作人员对灭火至关重要。案例研究表明，露天仓库发生火灾事故的损失比仓库发生类似火灾事故的损失更为严重。该模型为棉花储存火灾风险管理和紧急火灾事故中的决策提供支持。