Abstract
ABSTRACT In this study, the chromatographic characteristics of 100 different pyrethroids including ester derivatives of cyclopropanecarboxylic acids were analyzed by measuring their logarithmic kovats retention index (log KRI) using a quantitative structure-retention relationship (QSRR). The log KRI of the studied pyrethroids were modeled by genetic algorithm-structure retention relationships (GA-QSRR) based on linear and nonlinear regression models. The descriptors such as HNar, H0v, and H5p, which express the GETAWAY (geometry, topology, and atom-weights assembly) compound descriptors, have a reasonable correlation with the log KRI. We assessed the predictive strength of the BP-ANN model and demonstrated the potential of the model using various statistical parameters. The statistical parameters such as Q2F1, Q2F2, Q2F3 , AAD, RMSE and CCC were used to evaluate the predictive ability of the BP-ANN model. In predicting the log KRI of pyrethroids, the results indicated that the BP-ANN model is more reliable and accurate than the BW-MLR model.
Published Version
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