摘要
以直接橙S为研究对象,在因子设计的基础上,采用多因素方差分析法分析各因素对其水溶液光催化降解反应的影响,并以因子设计和Doehlert设计的实验数据为手段,建立模拟光催化降解直接橙S的BPNN模型。以用于预测实际降解体系,预测结果,相关系数R=0.9916,实验值与预测值的平均相对误差为4.24%。运用该模型分析光催化降解直接橙S的优化实验条件为pH=5、C_0=100 mg/L、[TiO_2]=1.3286 g/L,按此优化条件操作,测得直接橙S的30 min降解率为97.64%,与模型预测值95.58%相对误差仅为-2.11%,表明本文所建模型模拟直接橙S光催化降解反应效果良好。
Based on a factorial experimental design, the significant variables during the TiO2-photocatalytic degradation of Direct Orange S are studied by Multiple-way analysis of the variance. According to the experimental data of the factorial experimental design and Doehlert design, the BPNN model is built to predict an actual degradation system. The results have showed that the predicted correlation coefficient R is 0. 9916 and the mean relative error between the predictive value and experimental value is 4. 24%. The optimized experimental condition of the system is obtained: pH =5, Co = 100 mg/L and [TiO2 ] = 1. 3286 g/L. Under the optimized experimental condition in 30-minute degradation, the experimental value of the degradation rate is 97. 64% and the predictive value is 95.58%. The relative error is-2. 11%. The simulated result has showed that the BPNN can reach a good simulated effect on the TiO2-photoeatalytie degradation of Direct Orange S.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2008年第11期1359-1364,共6页
Computers and Applied Chemistry
关键词
直接橙S
光催化降解
BP神经网络
多因素方差分析
模拟
direct orange S, photoeatalytic degradation, BPNN, multiple-way analysis of the variance, simulate