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首页> 外文期刊>Talanta: The International Journal of Pure and Applied Analytical Chemistry >The study of the relationship between the new topological index A_m and the gas chromatographic retention indices of hydrocarbons by artificial neural networks
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The study of the relationship between the new topological index A_m and the gas chromatographic retention indices of hydrocarbons by artificial neural networks

机译:用人工神经网络研究新拓扑指数A_m与烃的气相色谱保留指数的关系。

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摘要

The newly developed topological indices A_(ml)-A_(m3)and the molecular connectivity indices ~mX were applied to multivariate analysis in structure-property correlation studies.The topological indices calculated from the chemical structures of some hydrocarbons were used to represent the molecular structures.The prediction of the retention indices of the hydrocarbons on three different kinds of stationary phase in gas chromatography can be achieved applying artificial neural networks and multiple linear regression models.The results from the artificial neural networks approach were compared with those of multiple linear regression models.It is shown that the predictive ability of artificial neural networks is superior to that of multiple linear regression method under the experimental conditions in this paper.Both the topological indices ~2X and A_(ml)can improve the predicted results of the retention indices of the hydrocarbons on the stationary phase studied.
机译:将最新开发的拓扑指数A_(ml)-A_(m3)和分子连通性指数〜mX应用于结构性质相关性研究中的多变量分析。从某些烃类的化学结构计算出的拓扑指数用于表示分子可以使用人工神经网络和多元线性回归模型对气相色谱中三种固定相上烃的保留指数进行预测。将人工神经网络方法的结果与多元线性回归进行比较结果表明,在实验条件下,人工神经网络的预测能力优于多元线性回归方法。拓扑指数〜2X和A_(ml)均可改善保留指数的预测结果烃在固定相上的分布

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