期刊
RSC ADVANCES
卷 5, 期 9, 页码 6617-6624出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/c4ra14178d
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资金
- National Natural Science Foundation of China [21305108, 21375105]
- Natural Science Basic Research Plan in Shaanxi Province of China [2014JM2039]
- Innovative Research Team of Xi'an Shiyou University [2013QNKYCXTD01]
The quantitative structure property relationship (QSPR) for the photolysis half-life (t(1/2)) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) on spruce (Picea abies (L.) Karst.) needle surfaces under sunlight irradiation was investigated. Molecular distance-edge vector (MDEV) index was used as the structural descriptor of PCDD/Fs. The quantitative relationship between the MDEV index and log t(1/2) was modeled by using multivariable linear regression (MLR) and artificial neural network (ANN) respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction ability of the developed models. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation is 3.47 and 4.25 respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation is 2.68 and 3.52 respectively. It is demonstrated that there is a quantitative relationship between the MDEV index and log t(1/2) of PCDD/Fs. Both MLR and ANN are practical for modeling this relationship. The developed MLR model and ANN model can be used to predict the log t(1/2) of PCDD/Fs. Thus, the log t(1/2) of each PCDD/F congener was predicted by using the developed models.
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