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机构地区:[1]西安石油大学化学化工学院,陕西西安710065
出 处:《广东化工》2017年第12期32-33,共2页Guangdong Chemical Industry
基 金:中国石油科技创新基金No.2015D-5006-0407;国家级大学生创新创业训练计划项目No.201510705216;陕西省青年科技新星计划项目2016KJXX-16;西安石油大学青年科研创新团队项目No.2013QNKYCXTD01
摘 要:研究了烷烃密度的定量结构-性质关系。以电性拓扑状态指数为结构描述符,分别用多元线性回归(MLR)和人工神经网络(ANN)建立了结构描述符和密度之间的校正模型。用留一交叉验证和外部测试集验证评价所建立MLR和ANN模型的预测能力。对于MLR模型,这两种验证的均方根相对误差分别为3.37和1.92。对于ANN模型,这两种验证的均方根相对误差为1.06和1.34。这说明建立的MLR和ANN模型都可用于预测烷烃的密度,但ANN模型优于MLR模型。The quantitative structure property relationship (QSPR) for the density of alkanes was investigated. Electrotopological state (ETS) index was used as the structural descriptor. The relationship between the ETS index and density was modeled with multivariate linear regression (MLR) and artificial neural network (ANN) respectively. Leave one out cross validation (Loo-CV) and external test set validation (EV) were conducted to assess the prediction performance of the developed models. For the MLR model, the root mean square relative error (RMSRE) of Loo-CV and EV is 3.37 and 1.92 respectively. For the ANN model, the RMSRE of Loo-CV and EV is 1.06 and 1,34 respectively. It is demonstrated that there is a quantitative relationship between the ETS index and density. Both MLR and ANN are practicable for modeling this relationship.
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