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Quantitative prediction of substituted products based on quantum-chemical parameters and neural network method
Authors:WANG  Xue-Ye SONG  HuangCollege of Chemistry  Chemical Engineering  Xiangtan University  Xiangtan  Hunan   China
Affiliation:WANG,Xue-Ye SONG,HuangCollege of Chemistry and Chemical Engineering,Xiangtan University,Xiangtan,Hunan 411105,China
Abstract:
The criterion of orientating group of electrophilic aromatic nitration was discussed by means of pattern recognition method with quantum-chemical parameters as features, and the product ratios of the reactions were quantitatively calculated using artificial neural network (ANN) method with the same parameters as inputs, based on the ab initio calculation of quantum chemistry. The quantum-chemical parameters involved orbital energy, orbital electron population, atomic total electron density and atomic net charge. The predicted values are in agreement with experimental results and (he predicted error of the ANN with quantum-chemical parameters for the reaction is the smallest among the all methods.
Keywords:Product ratio   quantitative structure-activity relationship   artificial neural network   quantum-chemical parameters
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