改进的LM-BP算法预测活性染料染色K/S值  

K /S value prediction of reactive dyes with improved LM-BP algorithm

作　　者：郑春玲[1] 姜会钰[2] 

机构地区：[1]南京工业大学食品与轻工学院,江苏南京211800 [2]武汉科技学院化学工程学院,湖北武汉430073

出　　处：《纺织学报》2010年第8期82-85,共4页Journal of Textile Research

摘　　要：针对标准BP算法收敛速度慢,易出现局部极小值等缺陷,采用Levenberg-Marquardt(LM-BP)算法,提出了一种经改进的BP神经网络预测模型。运用该预测模型,建立了活性染料染色各工艺参数与织物表面K/S值之间的对应关系,同时将其与传统BP算法预测模型在网络收敛时间、预测准确度等方面进行比较。结果表明:传统BP算法经1 500步训练后达到的收敛精度,在LM-BP算法预测模型中只需大约7步训练;染色K/S值预测值和试验值之间的相关系数R也相应由0.995提高到0.999。对比认为,LM-BP算法预测模型在对活性染料染色K/S值的预测中更为优越,时间短,准确率高。An improved prediction model using Levenberg-Marquardt（LM-BP） algorithm was carried out to make up for some defects such as slow convergence speed and local minimum point in traditional algorithm of BP neural network.The new prediction model was applied to indicate the relationship between various technical parameters and K /S values in dyeing with reactive dyes.Meanwhile,the convergence time and predictive precision of both prediction models were compared.The results revealed that LM-BP network model achieved the required precision after about 7 steps training while more than 1 500 steps were needed in traditional BP network model.The correlation coefficient between predictive and experimental K /S values was improved from 0.995 to 0.999 accordingly.It was considered that LM-BP method was superior in the prediction by K /S values of reactive dyes,with short time and high precision.

关 键 词：K/S值 活性染料 BP神经网络 LM-BP算法 预测模型 

分 类 号：TS193.13[轻工技术与工程—纺织化学与染整工程]