AIChE Journal · 2009 · 46 citations · 18 references
Natural SciencesChemistryComputational ChemistryTheoretical ChemistryThermal AnalysisFuel CharacteristicsMaterial ModelingMolecular DescriptorsMolecular Property PredictionStructure-property RelationshipsAutoignition TemperatureComputational Prediction ModelsFlammability LimitsFlash PointGenetic Algorithm OptimizationQuantitative Structure - Property Relationship ModelingQuantitative Structure-property Relationship ModelsStructure-property Relationship Analysis
Abstract A quantitative structure‐property relationship study is performed to develop mathematical models for predicting the flammability characteristics of pure hydrocarbons. The molecular structures of the compounds are numerically represented by various kinds of molecular descriptors. Genetic algorithm based multiple linear regression is used to select most statistically effective descriptors on the flash point, the autoignition temperature, and the lower and upper flammability limits of hydrocarbons, respectively. The resulted models are four multilinear equations. These models are very simple and can predict the flash point, the autoignition temperature, and the lower and upper flammability limits for the test set with average absolute errors of 5.41 K, 28.00 K, 0.044 vol %, and 0.503 vol %, respectively. The models are further compared with other published method and are shown to be more superior. The proposed method can be used to predict the flammability characteristics of hydrocarbons from the knowledge of only the molecular structures. © 2009 American Institute of Chemical Engineers AIChE J, 2010
18
Principles of QSAR models validation: internal and external
Paola Gramatica · QSAR & Combinatorial Science · 2007 · 2.2K citations · Full text
Alan R. Katritzky, Uko Maran, Victor S. Lobanov et al. · Journal of Chemical Information and Computer Sciences · 1999 · 270 citations