Study on quantitative structure-property relationship of organics would be helpful in researching for equeous solubility and octanal-water partition coefficients of organics.
研究有机物的定量结构-性质关系将有助于研究有机物的均等溶解度和辛酸-水分配系数。
A quantitative structure-property relationship (QSPR) model based on artificial neural networks was established to predict the flash points of fatty alcohols.
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。
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。
Study on quantitative structure-property relationship (QSPR) of organics would be helpful in researching for equeous solubility (pS) and octanal-water partition coefficients (logKsw) of organics.
基于定量结构-性质关系（QSPR）研究有机物的性质具有重要意义。
The developed quantitative formula can be applied to predict the biodegradation values of LAS and to help disclose structure-property relationship of chemical compounds.
应用这一定量关系式， 能够合理表征LAS的结构性能关系， 且有助于揭示化合物结构与性能之间的关系。
Prediction of the critical volume of alkenes using a quantitative structure property relationship;
提出了一种基于元素和化学键的估算有机物临界体积的新方法。
Prediction of the critical volume of alkenes using a quantitative structure property relationship;
提出了一种基于元素和化学键的估算有机物临界体积的新方法。
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