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QSBR study of substituted phenols and benzoic acids 被引量:1

QSBR study of substituted phenols and benzoic acids
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摘要 The biodegradability of 30 substituted phenols and benzoic acids was determined by BOD technique. The molecular weight ( M W), heat of formation ( H f) and the energy of the highest occupied molecular orbital ( E HOMO ) of the studied compounds were calculated by the quantum chemical method MOPAC6 0 AM1. The quantitative structure biodegradability relationships (QSBRs) were developed by the linear regression method and neural network approach, respectively. It has been shown that the neural network method is able to provide a superior fit to the training set data and test set data and produce a lower prediction error than the linear regression method. The biodegradability of 30 substituted phenols and benzoic acids was determined by BOD technique. The molecular weight ( M W), heat of formation ( H f) and the energy of the highest occupied molecular orbital ( E HOMO ) of the studied compounds were calculated by the quantum chemical method MOPAC6 0 AM1. The quantitative structure biodegradability relationships (QSBRs) were developed by the linear regression method and neural network approach, respectively. It has been shown that the neural network method is able to provide a superior fit to the training set data and test set data and produce a lower prediction error than the linear regression method.
出处 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2003年第1期88-91,共4页 环境科学学报(英文版)
基金 TheNationalNaturalScienceFoundationofChina (No .2 98770 0 4 )andtheScienceInnovationFoundationofHohaiUniversity (No .10 4 3 4 0 110 0 )
关键词 BOD regression artificial neural network PREDICTION BOD regression artificial neural network prediction
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