摘要
提出了应用人工神经网络技术进行抄纸浆料配比优化的方法,介绍了优化原理和过程。以卷烟纸为例,建立了多种浆料的配比与纸张主要物理性能指标之间的人工神经网络模型。该模型比传统回归模型有着更高的预测精度。以此模型为基础,通过扫描仿真,获得了针叶木浆、麻浆及填料配抄生产卷烟纸的各组分的配比范围,并从中优选出最佳配比。
Artificial Neural Network (ANN) was applied to optimize the of paper formulation. The theory and process were described. ANN model between paper physical characteristics and the formulation of cigarette paper was established. The model had higher prediction precision compared with traditional regression model. The optimum formulation of the paper was found based on the information about the different ratio of various components of the cigarette paper such as softwood pulp, hemp pulp and filler obtained through scanning simulation. The satisfactory results showed that the new method was practicable.
出处
《中国造纸》
CAS
北大核心
2005年第5期44-46,共3页
China Pulp & Paper
