[1]任保增,李晨,袁晓亮,等.三聚氰酸在水中溶解度的测定与关联[J].郑州大学学报(工学版),2003,24(02):19-21,32.[doi:10.3969/j.issn.1671-6833.2003.02.005]
　Ren Baozeng,LI Chen,Yuan Xiaoliang,et al.Determination and correlation of solubility of cyanic acid in water[J].Journal of Zhengzhou University (Engineering Science),2003,24(02):19-21,32.[doi:10.3969/j.issn.1671-6833.2003.02.005]

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三聚氰酸在水中溶解度的测定与关联()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

24

期数:

2003年02期

页码:

19-21,32

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

Determination and correlation of solubility of cyanic acid in water

作者:

任保增; 李晨; 袁晓亮; 等.

郑州大学化工学院,河南,郑州,450002, 郑州大学化工学院,河南,郑州,450002, 郑州大学化工学院,河南,郑州,450002, 郑州大学化工学院,河南,郑州,450002, 郑州大学化工学院,河南,郑州,450002

Author(s):

Ren Baozeng; LI Chen; Yuan Xiaoliang; etc

关键词:

三聚氰酸;  RBF神经网络;  溶解度;  模型

Keywords:

Cyanuric acid;  RBF neural networks;  solubility;  Model

DOI:

10.3969/j.issn.1671-6833.2003.02.005

文献标志码:

A

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+(18 932.949 4)/(T)+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283.15～363.15 K间是适用的.

Abstract:

Using the equilibrium method, the solubility of cyanic acid in water was determined, and the data correlated with the Apelblat solubility equation was: lnx=-474.8025+(18 932.949 4)/(T)+70.7514lnT, and the average relative error between the calculated value and the experimental value and the literature value was 1.28%.Using temperature as the input vector and solubility as the output vector, RBF neural network was established, and the results showed that The function approximation of RBF neural network can achieve fast convergence of the network, and the average error of the training set is 0.81% and the average error of the test set is 1.64%.

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