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高层建筑电气火灾隐患因子定量分析方法研究
引用本文:李华,朱瑕.高层建筑电气火灾隐患因子定量分析方法研究[J].中国安全生产科学技术,2018,14(12):124-129.
作者姓名:李华  朱瑕
作者单位:(西安建筑科技大学 资源工程学院,陕西 西安 710055)
基金项目:基金项目: 西安建筑科技大学青年科技基金项目(QN0619);学科建设重点培育计划项目(XK201812)
摘    要:为了对高层建筑电气火灾隐患排查进行定量化分析,采用解释结构模型构建高层建筑电气火灾隐患因子的复杂逻辑模型;在利用德尔菲法确定隐患因子初始概率的基础上,经过交叉影响分析法求解交叉影响概率矩阵;引入马尔科夫链修正各隐患因子交叉影响后的概率,得到火灾隐患因子的稳态概率矩阵。研究结果表明:各隐患因子的马尔科夫链校正概率比德尔菲法测定的初始概率更加准确,该计算排序结果可明确高层电气火灾隐患排查和管控的重点。

关 键 词:高层建筑  电气火灾  解释结构模型(ISM)  交叉影响分析法(CIA)  马尔科夫链预测法

Research on quantitative analysis method for hidden trouble factors of electrical fire in high rise buildings
LI Hua,ZHU Xia.Research on quantitative analysis method for hidden trouble factors of electrical fire in high rise buildings[J].Journal of Safety Science and Technology,2018,14(12):124-129.
Authors:LI Hua  ZHU Xia
Institution:(School of Resources Engineering, Xi’an University of Architecture and Technology, Xi’an Shaanxi 710055, China)
Abstract:In order to quantitatively analyze the hidden trouble of electrical fire in the high rise buildings, a complex logic model for the hidden trouble factors of electrical fire in the high rise buildings was constructed by using the interpretative structural modeling (ISM). Based on the initial probabilities of hidden trouble factors determined by the Delphi method, the cross impact probability matrix was solved by using the cross impact analysis (CIA) method. The probabilities of each hidden trouble factor under the cross impact was corrected by introducing into the Markov chain, and the steady state probability matrix of the fire hidden trouble factors was obtained. The results showed that the corrected probability by the Markov chain of each hidden trouble factor was more accurate than the initial probability determined by the Delphi method, and the sorting results of the calculation could make clear the key points of investigation and control for the hidden trouble of electrical fire in the high rise buildings.
Keywords:high rise building  electrical fire  interpretative structural modeling (ISM)  cross impact analysis (CIA) method  Markov chain prediction method
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