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基于支持向量机的导管泄爆容器压力峰值预测
引用本文:张庆武,蒋军成,喻源,崔益虎.基于支持向量机的导管泄爆容器压力峰值预测[J].爆炸与冲击,2014,34(6):748-753.
作者姓名:张庆武  蒋军成  喻源  崔益虎
作者单位:南京工业大学城市建设与安全工程学院,江苏 南京210009
基金项目:the National Natural Science Foundation of China,国家自然科学基金项目,江苏省高校自然科学基金项目,江苏省2012年度普通高校研究生科研创新计划项目
摘    要:为了预测导管泄爆容器压力峰值,根据文献提取出影响导管泄爆容器压力峰值的因素,将这些因素作为输入变量,采用支持向量机算法对压力峰值与各因素的内在关系进行了研究,建立导管泄爆容器压力峰值预测模型,对模型的有效性及预测能力进行了验证。将预测模型与现有经验公式进行比较,表明支持向量机模型具有较好的预测能力,且预测能力优于经验公式。

关 键 词:爆炸力学    压力峰值    支持向量机    泄爆容器    导管    气体爆炸
收稿时间:2013-04-12

Prediction of peak pressure in the explosion-vented vessel with a venting duct based on support vector machine
Zhang Qing-wu,Jiang Jun-cheng,Yu Yuan,Cui Yi-hu.Prediction of peak pressure in the explosion-vented vessel with a venting duct based on support vector machine[J].Explosion and Shock Waves,2014,34(6):748-753.
Authors:Zhang Qing-wu  Jiang Jun-cheng  Yu Yuan  Cui Yi-hu
Institution:School of Urban Construction and Safety Engineering, Nanjing University of Technology, Nanjing210009, Jiangsu, China
Abstract:To predict the peak pressure in the explosion-vented vessel with a venting duct, the influencing factors on the peak pressure were abstracted from the experimental data in literatures.The abstracted factors were deployed as the inputs to the support vector machine(SVM), and the corresponding peak pressures were used as the outputs.Thereby, the SVM model was developed.The validity of the SVM model was checked by comparing the predictive capacities between the SVM model and the empirical formula.The results show that the SVM model has a better predictive capacity than the empirical formula.
Keywords:mechanics of explosion  peak pressure  support vector machine  explosion-vented vessel  venting duct
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