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基于模糊模式识别的模糊综合评价在高层建筑火灾危险评价中的应用
引用本文:刘爱华,施式亮,吴超. 基于模糊模式识别的模糊综合评价在高层建筑火灾危险评价中的应用[J]. 中国安全科学学报, 2005, 15(11): 103-107
作者姓名:刘爱华  施式亮  吴超
作者单位:1. 湖南科技大学能源与安全工程学院,湘潭,411201
2. 中南大学资源与安全工程学院,长沙,410083
基金项目:国家自然科学基金资助(50274060)
摘    要:针对高层建筑火灾危险的特点,建立了高层建筑火灾危险评价的指标体系,并应用层次分析法确定了其权重。根据高层建筑火灾危险评价系统具有多因素、多层次的特点,采用模糊综合评价方法;针对模糊综合评价的不足之处,提出把权广义距离之和最小模糊模式识别运用到模糊综合评价当中,建立了基于模糊模式识别的模糊综合评价模型;该评价模型避免了单因素矩阵的确定和模糊算子的选择问题,用安全状态特征值来表征最终的评价结果,能使评价结果更加准确,可操作性强。通过对陕西某高层建筑火灾危险评价实例证明,该模型具有较好的应用价值,为日常的安全管理和性能化防火设计提供了有用依据。

关 键 词:高层建筑火灾  模糊综合评价  模糊模式识别  相对隶属度
文章编号:1003-3033(2005)11-0103-05
收稿时间:2005-04-21
修稿时间:2005-08-12

Application of the Fuzzy Recognition Based Fuzzy Synthetic Assessment to High Building Fire Risk Assessment
LIU Ai-hua,SHI Shi-liang,WU Chao. Application of the Fuzzy Recognition Based Fuzzy Synthetic Assessment to High Building Fire Risk Assessment[J]. China Safety Science Journal, 2005, 15(11): 103-107
Authors:LIU Ai-hua  SHI Shi-liang  WU Chao
Abstract:According to the characteristics of the high building fire hazard,the index system of the high building fire hazard assessment is established,and its weighting is determined by hierarchic analysis.Fuzzy synthetic assessment is adopted since the high building fire hazard assessment system has the characteristics of multiple factors and multiple levels.Due to the shortcomings of the fuzzy synthetic assessment,the fuzzy recognition theory is suggested to be used into the fuzzy synthetic assessment to establish fuzzy recognition fuzzy synthetic assessment based on model.This model could avoid the determination of single factor matrix and the option of fuzzy calculation unit,and the final assessment result is expressed by the value of safety status features,which makes the assessment result more accurate and more operational.The exemplification of this model in a high building fire risk in Shanxi province proves that the model shows better practicability and could provide valuable criteria for routine safety management and performance fire-fighting design.
Keywords:high building fire risk  fuzzy synthetic assessment  fuzzy recognition  relative subordinate degree
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