建立了一个基于人工神经网络方法的定量结构-性质相关性(QSPR)研究模型，用于预测脂肪醉闪点。
A quantitative structure-property relationship (QSPR) model based on artificial neural networks was established to predict the flash points of fatty alcohols.
结果表明，所建定量结构性质相关（QSPR）模型的相关性高、稳健性好、预测能力强。
These results demonstrate that the quantitative structure-property relationship(QSPR) models have a high correlativity, fine stability and precise predictability.
结果表明，所建定量结构性质相关（QSPR）模型的相关性高、稳健性好、预测能力强。
These results demonstrate that the quantitative structure-property relationship(QSPR) models have a high correlativity, fine stability and precise predictability.
应用推荐