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基于支持向量机的室内轰燃预测模型研究
引用本文:王成武.基于支持向量机的室内轰燃预测模型研究[J].中国安全科学学报,2011,21(4).
作者姓名:王成武
作者单位:宁夏消防总队 石嘴山市消防支队,宁夏石嘴山,753000
摘    要:为对室内轰燃进行准确预测,针对室内轰燃样本的不足在一定程度上制约了其应用,为此运用SVM技术构建室内轰燃预测的数学模型。在小样本条件下,应用工具软件LIBSVM进行仿真,并将SVM模型预测结果和人工神经网络预测结果进行对比。结果显示,SVM技术能较好地解决小样本和模型预测精确度之间的矛盾,SVM模型其预测精度及可行性高于神经网络模型。实例表明,由于室内火灾受多种因素影响,传统的预测方法存在一定的局限性,而SVM模型预测法预测的结果与试验结果比较一致。

关 键 词:火灾  支持向量机(SVM)  LIBSVM软件  轰燃  预测

Study on Predicting Model for Indoor Flashover Based on Support Vector Machine
WANG Cheng-wu.Study on Predicting Model for Indoor Flashover Based on Support Vector Machine[J].China Safety Science Journal,2011,21(4).
Authors:WANG Cheng-wu
Institution:WANG Cheng-wu(Shizuishan City Fire Department,Fire Division of Ningxia Province,Shizuishan Ningxia753000,China)
Abstract:In order to accurately predict flashover,based on the fact that insufficient samples restrict the knowledge-based method to some extent on predicting the flashover,a mathematical model for predicting indoor flashover was built using SVM technology.Under the condition of only a small quantity of samples,the application tool software LIBSVM was used to simulate the flashover prediction model and artificial neural network prediction model.The result shows that the SVM model can solve the contradiction of preci...
Keywords:fire  support vector machine(SVM)  LIBSVM software  flashover  prediction  
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