THE QSRR STUDY OF POLYCYCLIC AROMATIC HYDROCARBONS BY USING ANN METHOD

• 作 者: XiaotongZHANG[1]XinZHANG[2]QiangLI[2]ZhaolinSUN[2]LijuanSONG[2]TingSUN[3]
• 机 构: Liaoning Key Laboratory of Petrochemical Engineering,Liaoning Shihua University,113001 Fushun,Liaoni
• 出 处: BCEIA2013第十五届北京分析测试学术报告会(分析仪器应用技术报告会)
• 发表日期: 2013年期

　　Quantitative structure-retention relationship (QSRR) study was performed forpredicting the gas chromatography retention indices of 96 polycyclic aromatichydrocarbons (PAHs) on SE-52 capillary columns.First,descriptors werecalculated using Materials Studio (MS) software.Then the best-fittingdescriptors were selected by using stepwise multiple linear regression(SW-MLR).Then QSRR models were built by adopting multiple linearregression (MLR) and back propagation-artificial neural network(BP-ANN).The results showed prediction correlation coefficient R of 0.9971and 0.9976 for MLR and BP-ANN respectively.