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基于灰色-BP神经网络理论的上染率模型研究 被引量:1

Research on Dye-uptake Rate Model Based on Gray-BP Neural Network Theory
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摘要 以活性黄3RE上染棉织物为例,首先利用灰色系统GM(1,1)和Verhulst建立起上染率-染色工艺单因素模型,再将其输出直接作为神经网络的输入,最终建立灰色-BP神经网络上染率-染色工艺多因素模型,其拟合值的相对误差小于1.3%,并通过实验验证,预测值的误差均在1.0%以内。验证结果表明,该数学模型精确度较高,能较准确地反映棉织物活性染料染色后的上染率,并可以满足预测上染率的需求。 This paper takes dyeing of cotton fabric with Reactive Yellow 3RE for example.Firstly,dye-uptake rate and dying single-factor model was established with gray system GM(1,1)and verhulst.Secondly,the output directly served as the input of neural network,and finally dye-uptake rate and dying multi-factor model based on gray-BP neural network was established.The relative error of the fitting values was less than 1.3%.The experimental result shows that the error of the predicted value is within1.0%.The verification results show that the mathematical model has high accuracy and can exactly reflect the dye-uptake rate of reactive dyes in the dyeing process and meet the actual requirement of forecasted dye-uptake rate.
出处 《浙江理工大学学报(自然科学版)》 2014年第4期343-347,353,共6页 Journal of Zhejiang Sci-Tech University(Natural Sciences)
基金 国家自然科学基金(61074154)
关键词 活性染料 棉织物 灰色-BP神经网络 上染率 多因素模型 reactive dyes cotton fabric Grey-BP neural network dye-uptake rate multi-factor model
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