Support vector regression based QSPR for the prediction of some physicochemical properties of alkyl benzenes
Author:
Publisher
Elsevier BV
Subject
Physical and Theoretical Chemistry,Condensed Matter Physics,Biochemistry
Reference20 articles.
1. QSAR study with steric (MTD), electronic and hydrophobicity parameters on psychotomimetic phenylalkylamines
2. Maximum topological distances based indices as molecular descriptors for QSPR. Part 1. Application to alkyl benzenes boiling points
3. QSPR models of boiling point, octanol–water partition coefficient and retention time index of polycyclic aromatic hydrocarbons
4. Radial basis function neural network based QSPR for the prediction of critical pressures of substituted benzenes
5. Quantitative structure-property relationships for octanol–air partition coefficients of polychlorinated naphthalenes, chlorobenzenes and p,p′-DDT
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