Abstract

The quantitative structure property relationship (QSPR) for the relative retention time (RRT) of polybrominated diphenyl ethers (PBDEs) was investigated. Molecular distance-edge vector (MDEV) index was used as the structural descriptor of PBDEs. The quantitative relationship between the MDEV index and RRT of PBDEs was modeled by using multivariate linear regression (MLR), partial least square (PLS) and radial basis function artificial neural network (RBF-ANN) respectively. Three QSPR models, MLR model, PLS model and RBF-ANN model, were established. External validation was carried out to assess the predictive ability of the developed models. The investigated 126 PBDEs were randomly divided into two groups: a calibration set, which comprises 88 PBDEs, and a test set, which comprises 38 PBDEs. For the MLR model, the prediction RMSRE of test set is 12.58. For the PLS model, the prediction RMSRE of test set is 12.58. For the RBF-ANN model, the prediction RMSRE of test set is 8.21. It is demonstrated that the MDEV index of PBDEs is quantitatively related to the RRT of PBDEs. The developed three models are all practicable for predicting the RRT of PBDEs. Compared with the MLR and PLS models, the RBF-ANN model shows higher prediction accuracy.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.