基于MLP-ANN和SVM方法的多氯代二苯并呋喃光解半衰期QSPR比较研究
A Comparative QSPR Study on Photolysis Half-lives of Polychlorinated Dibenzofurans by MLP-ANN and SVM
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摘要: 多氯代二苯并呋喃（PCDFs）是全球性污染物之一，光化学降解是其主要的环境降解途径。基于分子二维拓扑结构提出的用于表征化合物结构参数的分子电性距离矢量描述子（MEDV），应用多层感知器神经网络（MLP-ANN）和支持向量机（SVM）对PCDFs在云杉针叶和飞灰表面的光解半衰期（t1/2）进行定量结构-性质相关（QSPR）分析，并用交互检验和外部样本对所建模型的稳定性进行了检验。旨在为PCDFs光解机理的QSPR研究提供新思路。结果表明，所建模型均具有良好的稳定性和预测能力，尤以MLP-ANN模型为佳，其建模相关系数（Rcum）、留一法交互检验相关系数（QLOO）以及外部样本检验相关系数（Qext）分别为0.850、0.816、0.954（云杉针叶表面）和0.892、0.753、0.897（飞灰表面）。
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关键词:
- 多氯代二苯并呋喃(PCDFs) /
- 分子电性距离矢量(MEDV) /
- 光解半衰期 /
- QSPR /
- 多层感知器神经网络(MLP-ANN) /
- 支持向量机(SVM)
Abstract: Environmental pollution by polychlorinated dibenzofurans (PCDFs) is one of the global environment issue. Photolysis is the main pathway of PCDFs degradation in the environment. In this paper, molecular electronegativity distance vector (MEDV) descriptors, based on two-dimensional topological structure, are used to describe the structures of PCDFs compounds. Using multilayer perceptron neural network (MLP-ANN) and support vector machine (SVM), a quantitative structure-property relationship (QSPR) study was performed to correlate the photolysis half-lives (t1/2) of PCDFs adsorbed on the spruce needles and fly ash surfaces with their molecular structures. Meanwhile, the stability of the model was tested by cross validation and the external validation of the test samples. The aim of this study is to provide a new idea or method reference for QSPR study on the photolysis mechanism of PCDFs. The established models, especially the MLP-ANN model showed good stability and predictive ability. The correlation coefficients including cumulative multiple correlation coefficient of training set (Rcum, cumulative cross-validated Rcum of training set QLOO and external Q of test set Qext) of the MLP-ANN model are 0.850, 0.816, 0.954 (spruce needles) and 0.892, 0.753, 0.897 (flying ash surface), respectively. -
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