Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Investigation of Retention Behaviors of Essential Oils by Using QSRR

(2010) Investigation of Retention Behaviors of Essential Oils by Using QSRR. Journal of the Chinese Chemical Society. pp. 982-991. ISSN 0009-4536

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Abstract

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) technique were used to investigate the correlation between retention index (RI) and descriptors for diverse compounds in essential oils. The correlation coefficient cross validation (Q(2)) between experimental and predicted retention index for training and test sets by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.948, 0.924, 0.958 and 0.980 (for training set), 0.917, 0.890, 0.915 and 0.954 (for test set), respectively. The L-M ANN model with the final optimum network architecture of 5-2-1 gave a significantly better performance than the other models. This indicates that L-M ANN can be used as an alternative modeling tool for quantitative structure-property/retention relationship (QSPR/QSRR) studies.

Item Type: Article
Keywords: Essential oils QSRR Genetic algorithm KPLS L-M ANN artificial neural-network genetic-algorithm gas-chromatography regression prediction selection pls components lamiaceae indexes Chemistry
Divisions:
Page Range: pp. 982-991
Journal or Publication Title: Journal of the Chinese Chemical Society
Journal Index: ISI
Volume: 57
Number: 5A
Identification Number: https://doi.org/10.1002/jccs.201000137
ISSN: 0009-4536
Depositing User: مهندس مهدی شریفی
URI: http://eprints.medilam.ac.ir/id/eprint/869

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