Journal
ANNALI DI CHIMICA
Volume 97, Issue 1-2, Pages 69-83Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adic.200690087
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Quantitative structure property relationship (QSPR) analysis has been directed to a series of pure nonionic surfactants containing linear alkyl, cyclic alkyl, and alkey phenyl ethoxylates. Modeling of cloud point of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and partial least squares (PLS) regression. In this study, a genetic algorithm (GA) was applied as a variable selection method in QSPR analysis. The results indicate that the GA is a very effective variable selection approach for QSPR analysis. The comparison of the two regression methods used showed that PLS has better prediction ability than MLR.
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