| Literature DB >> 19544192 |
Abstract
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.Entities:
Mesh:
Substances:
Year: 2009 PMID: 19544192 DOI: 10.1080/10629360902949534
Source DB: PubMed Journal: SAR QSAR Environ Res ISSN: 1026-776X Impact factor: 3.000