摘要
采用前馈线性网络BP算法,计算了Cd2+-OH-CO2-3三元体系的累积稳定常数。用Hopfield反馈网络研究了体系中络合物的形态分布。溶液中溶解的CO2对Igβ1的计算结果有重要影响,对Igβ2,Igβ3,Igβ4的结果影响不大。通过对CO2-3 影响的校正,较好地改善了神经网络法计算Igβ1的结果。
The accumulative stabilization constants and the species distribution in Cd2- OH--CO2-3 system were calculated respectively by the feed-forward linear neural network with back-propagation algorithm and by Hopfield feedback network. The presence of CO2 in the solution has serious effect on the calculation results of Igβ1, and of species distribution, while having no obvious effect on that of Igβ2, Igβ3, Igβ4. The calculation result of Igβ1 can be well improved by calibrating the effect of carbonate in aquatic system.
出处
《分析化学》
SCIE
EI
CAS
CSCD
北大核心
1997年第4期400-403,共4页
Chinese Journal of Analytical Chemistry
基金
国家自然科学基金
关键词
人共神经网络
累积稳定常数
镉
碳酸根
配合物
Artificial neural network, back-propagation algorithm, accumulative stabiliza- tion constant, cadmium, carbonate