Estimation of molecular diffusivity of pure chemicals in water: a quantitative structure-property relationship study
A quantitative structure-property relationship (QSPR) study was performed to predict the molecular diffusivity of pure chemicals in water. A genetic-algorithm-based multivariate linear regression (GA-MLR) was applied to select the most statistically effective molecular descriptors for
modelling the molecular diffusivity of pure chemicals in water. Based on the selected molecular descriptors, a three-layer feed forward neural network (FFNN) was constructed to predict the property. The obtained results showed that the FFNN was able to predict the molecular diffusivity of
pure chemicals in water.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Department of Chemical Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran,Department of Chemical Engineering, Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, Tehran, Iran
Division of Polymer Science and Technology, Research Institute of Petroleum Industry (RIPI), P.O. Box 18745-4163, Tehran, Iran
April 1, 2009