基于PCA-FPP-BP神经网络的高层建筑火灾安全评价 |
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引用本文: | 牛发阳,段美栋,王建波,姜东民,杨冠楠. 基于PCA-FPP-BP神经网络的高层建筑火灾安全评价[J]. 工业安全与环保, 2016, 0(7): 26-29. DOI: 10.3969/j.issn.1001-425X.2016.07.008 |
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作者姓名: | 牛发阳 段美栋 王建波 姜东民 杨冠楠 |
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作者单位: | 1. 青岛理工大学管理学院 山东青岛266520;2. 中建三局总承包公司郑州分公司 郑州450000 |
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基金项目: | 国家自然科学基金(71471094),山东省自然科学基金(ZR2011GL021)。 |
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摘 要: | 为解决高层建筑构造复杂、人员密度大、火灾触发因素繁多而造成高层建筑火灾安全评价困难的问题,本文提出基于PCA-FPP-BP神经网络的高层建筑火灾安全评价模型。首先运用主成分分析(PCA)对构建的高层建筑火灾安全评价指标降维处理,筛选主要信息;接着基于三角模糊数构建模糊评判矩阵,利用模糊优先规划(FPP)求解指标的权重值,减少主观的影响;最后考虑到指标间关系错综复杂彼此交叉和反馈的特性,选择BP神经网络对高层建筑火灾安全进行评价。通过工程案例证明该评价模型的实用性以及可靠性。
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关 键 词: | 高层建筑 火灾 安全评价 模糊优先规划 BP神经网络 |
Fire Safety Assessment of High Rise Building Based on PCA -FPP-BP Neural Network |
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Abstract: | In order to solve the difficult problem of the high -rise building fire safety evaluation caused by the complex high-rise building structure ,personnel density and various fire -caused factors ,this paper proposes a high-rise building fire safety assessment model based on PCA-FPP-BP neural network .Firstly ,the principal component analysis (PCA) is used to reduce the dimension of the building fire safety evaluation index ,and the main information is selected ;then ,fuzzy judg-ment matrix is constructed based on triangular fuzzy number ,the weight value of the index is solved by fuzzy priority pro-gramming (FPP) and the subjective influence is reduced ;finally considering the complicated relations between indexes and the characteristics of cross each other and feedback ,the BP neural network is selected to evaluate the fire safety of high -rise buildings .The practicability and reliability of the evaluation model are proved through the engineering case . |
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Keywords: | high-rise building fire risk safety evaluation fuzzy preference programming BP neural network |
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