三聚氰酸在水中溶解度的测定与关联  

Determination and Correlation of Solubility of Cyanuric Acid in Water

作　　者：任保增[1] 李晨[1] 袁晓亮[1] 李伟然[1] 雒廷亮[1] 

机构地区：[1]郑州大学化工学院,河南郑州450002

出　　处：《郑州大学学报（工学版）》2003年第2期19-21,32,共4页Journal of Zhengzhou University（Engineering Science）

基　　金：1999年度河南省杰出青年科学基金资助项目(9909)

摘　　要：采用平衡法,测定三聚氰酸在水中的溶解度,其数据用Apelblat溶解度方程关联的结果为:lnx=-474.8025+18932.9494T+70.7514lnT,计算值与实验值、文献值间的平均相对误差为1.28%.以温度为输入矢量、溶解度为输出矢量,建立RBF神经网络,结果表明,RBF神经网络进行函数逼近可实现网络的快速收敛,训练集平均误差为0.81%,测试集平均误差为1.64%.因此,所建立的RBF人工神经网络模型对三聚氰酸-水体系在283.15～363.15K间是适用的.Solubility of cyanuric acid in water systematically is determined. By Apelblat's solubility equation correlating, the equation lnx=-474.802 5+18 932.949 4T+70.751 41lnT is obtained. The mean relative deviation is 1.28% between the calculated values and the experimental, literature values. Taking temperature as input vector and solubility as output vector to set up radial basis function artificial neural networks, the results indicate that RBF can fast realize convergence approaching a function. The mean relative deviation of train aggregate is 0.81%, and test aggregate is 1.64%. The RBF neural network is suitable for the system of cyanuric-water from 283.15 K to 363.15 K.

关 键 词：三聚氰酸 溶解度 Apelblat方程 平衡法 RBF神经网络 三聚氰胺 模型 

分 类 号：TQ226.63[化学工程—有机化工] TQ027.35