A novel QSPR model for prediction of lower flammability limits of organic compounds based on support vector machine

A quantitative structure-property relationship (QSPR) study is suggested for the prediction of lower flammability limits (LFLs) of organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structures of compounds, such as topological, charge, and geometric descriptors. Genetic algorithm was employed to select optimal subset of descriptors that have significant contribution to the overall LFL property. The novel chemometrics method of support vector machine was employed to model the possible quantitative relationship between these selected descriptors and LFL. The resulted model showed high prediction ability that the obtained root mean square error and average absolute error for the whole dataset were 0.069 and 0.051 vol.%, respectively. The results were also compared with those of previously published models. The comparison results indicate the superiority of the presented model and reveal that it can be effectively used to predict the LFL of organic compounds from the molecular structures alone.