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中文摘要：
运用神经网络偏最小二乘分别与遗传算法和主成分分析相结合，以含能材料的结构描述符和爆轰性能等参数，建立了“分子结构-爆轰性能”之间的定量关系预测模型，并对30种含能材料的密度和理论爆速进行了预测，其相对误差均在5％以下。表明这种方法为新型含能材料分子设计和爆轰性能预估提供了新的方法和手段。
英文摘要：
The methods have been developed for model construction of quantitative structure-detonation relationship by combining nerural network partial least squares with genetic algorithms and principal component analysis respectively. The model can predict the density and detonation velocity of 30 explosives, all the relative errors are less than 5%. The result shows that it offers novel method to design molecules and estimate the detonation relationship performance for new energetic materials.
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