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中文摘要：
以炸药分子的结构描述符和爆轰性能等参数,利用主成分分析（PCA）结合BP神经网络的方法,建立了炸药分子结构与爆速之间的定量关系预测模型,并对20种炸药的爆速进行了预测,其相对误差均低于9%。结果表明,所建立的模型较好地反映了炸药分子结构与爆速之间的关系,具有较高的预测精度。该方法为设计新型炸药分子时正确估算其爆速提供了一条新的途径。
英文摘要：
A quantitative structure-property relationship model of explosives detonation velocity was built by principal component analysis and artificial neural network with molecular structure descriptors.With the model a predicting test was made to a predicting-set of 20 explosives which didn＇t belong to the training-set,all the relative error less than 9%.The results showed that the yield model reflected the complex relationship between the structure and the detonation velocity,and had high predicting accuracy.This bring forward a novel method for estimating the detonation velocity when designing new explosives.
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