Hadi Noorizadeh1, Abbas Farmany. 1. Department of Chemistry, Faculty of Sciences, Arak Branch, Islamic Azad University, Arak, Iran. hadinoorizadeh@yahoo.com
Abstract
INTRODUCTION: A quantitative structure-retention relation (QSRR) study was conducted on the retention times of organic pollutants in textile wastewaters and landfill leachate which was obtained by liquid chromatography-reversed phase-atmospheric pressure chemical ionization-mass spectrometry. METHODS: The genetic algorithm was used as descriptor selection and model development method. Modeling of the relationship between selected molecular descriptors and retention time was achieved by linear (partial least square) and nonlinear (Levenberg-Marquardt artificial neural network, L-M ANN) methods. Linear and nonlinear models provide good results whereas more accurate results were obtained by the L-M ANN model. CONCLUSION: This is the first research on the QSRR of the organic pollutants in textile wastewaters and landfill leachate against the retention time.
INTRODUCTION: A quantitative structure-retention relation (QSRR) study was conducted on the retention times of organic pollutants in textile wastewaters and landfill leachate which was obtained by liquid chromatography-reversed phase-atmospheric pressure chemical ionization-mass spectrometry. METHODS: The genetic algorithm was used as descriptor selection and model development method. Modeling of the relationship between selected molecular descriptors and retention time was achieved by linear (partial least square) and nonlinear (Levenberg-Marquardt artificial neural network, L-M ANN) methods. Linear and nonlinear models provide good results whereas more accurate results were obtained by the L-M ANN model. CONCLUSION: This is the first research on the QSRR of the organic pollutants in textile wastewaters and landfill leachate against the retention time.