The quantitative structure activity relationship(QSAR) of 32 polychlorinated dibenzo-p-furans toxicity is set up with some quantum-chemical parameters calculated by HyperChem7.0 and self-designed structure descriptor ...The quantitative structure activity relationship(QSAR) of 32 polychlorinated dibenzo-p-furans toxicity is set up with some quantum-chemical parameters calculated by HyperChem7.0 and self-designed structure descriptor codes.The quantum-chemical parameters(Ehomo,Ehomo1,Elumo,logP),the structure descriptor codes(R1,R9) are selected by stepwise regression.The predicting model has a correlation coefficient(R) of 0.9451 and standard error(s) of 0.5172.The performance of the QSAR equation is tested by leave-one-out procedure(LOO),and the correlation coefficient R and standard error(s) are 0.9381 and 0.5448 respectively.It shows that the QSAR model has good stability and predictability.The study indicates that the quantum-chemical parameters(Ehomo,Ehomo1,Elumo,logP) are important factors that can influence the compound toxicity.The toxicity of the compound would reduce when R1and R9 exist.展开更多
[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the tr...[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the training set and the validation set,respectively.And back propagation neural network(BPNN)model is adopted in order to establish the model of photo-catalytic degradation about weak acidic dyes mixture of the GRS big red and weak acid red R.The best result shows that the correlation coefficient(R)is 0.9345 and the mean relative error between the predictive value and experimental value(MRE(%))is 3.23,for training set;the value of R is 0.9257,MRE(%)is 2.75,for the validation set.Besides,we discussed the influences of the pH,[TiO2],and t vs.DC% by the BPNN model.The optimized experimental condition obtained is pH=5.0,[TiO2]=1.50g/L,and t=40min based on the BPNN model,and combination with optimization of nonlinear constraints programming.The experimental value of DC is 99.23%,the predictive value is 98.98%,and the relative error is-0.25% between the predictive value and the experimental value,in the optimized experimental condition.Above all these indicate that the model can not only simulate the system of photo-catalytic degradation commendably but also can obtain the optimal experimental conditions.展开更多
The design of gasoline blending made a linear transformation of the set of variables comprising component octane number, component distillation process data, component proportion of blending gasoline,and additive quan...The design of gasoline blending made a linear transformation of the set of variables comprising component octane number, component distillation process data, component proportion of blending gasoline,and additive quantity.With a production-based data LSSVM and ν-SVR and RBFNN machine learning methods the prediction model for octane number was established, and the design was computerized for directing gasoline blending in a petroleum refinery.The experimental results showed that the mean of value of absolute error was 0.227RON,and the maximun absolute error was 0.480RON.The experiments with the absolute error within 0.3RON accounted for 76.2% of the total experiments while those with absolute error within 0.4RON accounts for 90.5% of total experiments.展开更多
文摘The quantitative structure activity relationship(QSAR) of 32 polychlorinated dibenzo-p-furans toxicity is set up with some quantum-chemical parameters calculated by HyperChem7.0 and self-designed structure descriptor codes.The quantum-chemical parameters(Ehomo,Ehomo1,Elumo,logP),the structure descriptor codes(R1,R9) are selected by stepwise regression.The predicting model has a correlation coefficient(R) of 0.9451 and standard error(s) of 0.5172.The performance of the QSAR equation is tested by leave-one-out procedure(LOO),and the correlation coefficient R and standard error(s) are 0.9381 and 0.5448 respectively.It shows that the QSAR model has good stability and predictability.The study indicates that the quantum-chemical parameters(Ehomo,Ehomo1,Elumo,logP) are important factors that can influence the compound toxicity.The toxicity of the compound would reduce when R1and R9 exist.
文摘[TiO2],t and pH are named as the independent variables and the percentage of decolor(DC%)as the dependent variable.A Box-Behnken design and U12(6×4×3)design with three factors were established to form the training set and the validation set,respectively.And back propagation neural network(BPNN)model is adopted in order to establish the model of photo-catalytic degradation about weak acidic dyes mixture of the GRS big red and weak acid red R.The best result shows that the correlation coefficient(R)is 0.9345 and the mean relative error between the predictive value and experimental value(MRE(%))is 3.23,for training set;the value of R is 0.9257,MRE(%)is 2.75,for the validation set.Besides,we discussed the influences of the pH,[TiO2],and t vs.DC% by the BPNN model.The optimized experimental condition obtained is pH=5.0,[TiO2]=1.50g/L,and t=40min based on the BPNN model,and combination with optimization of nonlinear constraints programming.The experimental value of DC is 99.23%,the predictive value is 98.98%,and the relative error is-0.25% between the predictive value and the experimental value,in the optimized experimental condition.Above all these indicate that the model can not only simulate the system of photo-catalytic degradation commendably but also can obtain the optimal experimental conditions.
文摘The design of gasoline blending made a linear transformation of the set of variables comprising component octane number, component distillation process data, component proportion of blending gasoline,and additive quantity.With a production-based data LSSVM and ν-SVR and RBFNN machine learning methods the prediction model for octane number was established, and the design was computerized for directing gasoline blending in a petroleum refinery.The experimental results showed that the mean of value of absolute error was 0.227RON,and the maximun absolute error was 0.480RON.The experiments with the absolute error within 0.3RON accounted for 76.2% of the total experiments while those with absolute error within 0.4RON accounts for 90.5% of total experiments.
