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用人工神经网络预测黑火药燃烧性能
引用本文:崔庆忠,焦清介,任慧,杨荣杰. 用人工神经网络预测黑火药燃烧性能[J]. 北京理工大学学报, 2007, 27(6): 541-545
作者姓名:崔庆忠  焦清介  任慧  杨荣杰
作者单位:北京理工大学,材料科学与工程学院,北京,100081;北京理工大学,爆炸科学与技术国家重点实验室,北京,100081
摘    要:利用人工神经网络算法建立了黑火药燃烧热力学参数的定量BP网络模型,通过10组配方的元素组成及其输出参数测试值对模型进行了训练,用另外9组配方的测试结果与相应的预测结果进行了对比研究. 结果表明,该方法能较好地对黑火药的燃烧参数进行预测,预测值和试验值误差小于7%,精度较高,可作为功能黑火药配方设计、输出特性参数预测的工具.

关 键 词:人工神经网络  烟火药  黑火药  燃烧性能  预测
文章编号:1001-0645(2007)06-0541-05
收稿时间:2006-12-07
修稿时间:2006-12-07

Predicting the Thermodynamic Parameters of Black Powder by Artificial Neural Network
CUI Qing-zhong,JIAO Qing-jie,REN Hui and YANG Rong-jie. Predicting the Thermodynamic Parameters of Black Powder by Artificial Neural Network[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2007, 27(6): 541-545
Authors:CUI Qing-zhong  JIAO Qing-jie  REN Hui  YANG Rong-jie
Affiliation:1. School of Materials Science and Engineering, Beijing Institute of Technology, Beijing 100081, China; 2. State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Abstract:An artificial neural network(ANN) model about thermodynamic parameters evaluation of black powder was set up.After being trained by a train-set containing 10 compositions,the BP model was used to predict the thermodynamic parameters of black powder,and the predicted values were compared with that of experiments.The results showed that the prediction errors are less than 7%,and the ANN model was capable of making accurate predictions of combustion parameters of black powder.
Keywords:artificial neural network   pyrotechnic composition   black powder   combustion performance   prediction
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