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过程神经网络法推测聚丙烯酰胺分子质量
Prediction of Molecular Mass of Polyacrylamide with Process Neural Networks
【摘要】 利用过程神经网络学习记忆建立了丙烯酰胺聚合反应的升温曲线 (温度随时间变化曲线 )与平均相对分子质量的关系 ,所推测的聚丙烯酰胺平均相对分子质量的误差在 2 %以内 ,表明该方法简单有效 ,可以节省大量的实验工作量 .
【Abstract】 A process neural network of learning and memory abilities, has been proposed in order to examine the relationship between the temperature time reaction curve and the molecuar mass of polyacrylamide (PAA). The relative error of the molecular mass of PAA predicted by the process neural network was in 2% lower than that measured by chemical method, implying that the method proposed is simple and effective for a molecular mass determination of PAA.
【关键词】 聚丙烯酰胺;
分子质量;
推测;
过程神经网络;
【Key words】 polyacrylamide; molecular mass; prediction; procedure neural networks;
【Key words】 polyacrylamide; molecular mass; prediction; procedure neural networks;
- 【文献出处】 应用化学 ,Chinese Journal of Applied Chemistry , 编辑部邮箱 ,2002年07期
- 【分类号】O633
- 【下载频次】70