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基于局部加权偏最小二乘的近红外光谱分析方法研究
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作者单位
马力文,郭拓,马晋芳,史庆龙,肖环贤 1.陕西科技大学电子信息与人工智能学院2.中山大学南沙研究院3.江西保利制药有限公司 
基金项目:陕西省科技计划项目(2020NY-172)
中文摘要:针对近红外光谱分析技术中分析对象非线性现象突出的情况,提出了一种新的模型计算方法——局部加权偏最小二乘法(LWPLS)。以安胎丸为研究对象,采用LWPLS算法进行其近红外定量模型的建立,并比较偏最小二乘法(PLS)与LWPLS两种算法建立定量模型的精度。结果测得两种算法建立的校正模型中,阿魏酸的模型相关系数(R2)分别为0.785 5、0.971 9,预测误差均方根(RMSEP)分别为0.126 6、0.043 8,相对预测误差(RE)分别为12.66%、9.18%;洋川芎内酯A的R2分别为0.886 4、0.964 9,RMSEP分别为0.114 8、0.077 1,RE分别为14.01%、7.81%,显示LWPLS算法建立的模型精度更高。研究表明,采用LWPLS算法可提高安胎丸定量模型的准确性,具有可推广性和广泛的应用性。
中文关键词:局部加权偏最小二乘法(LWPLS)  近红外光谱  偏最小二乘法(PLS);阿魏酸;洋川芎内酯A
 
Study on A Near Infrared Spectroscopy Modeling Method Based on Local Weighted Partial Least Squares
Abstract:A new model calculation method,local weighted partial least squares(LWPLS),was proposed to solve the problem of nonlinear phenomena in near infrared spectroscopy.Taking Antai pill as the research object,the quantitative model for Antai pill was established by LWPLS algorithm,and the accuracies of quantitative models established by PLS and LWPLS were compared.Results indicated that,the correlation coefficient(R2) of PLS and LWPLS algorithms for ferulic acid were 0.785 5 and 0.971 9,the root mean square errors of prediction(RMSEP) were 0.126 6 and 0.043 8,and the relative prediction errors(RE) were 12.66% and 9.18%,respectively,while the R2 values of PLS and LWPLS algorithms for senkyunolide A were 0.886 4 and 0.964 9,the RMSEP values were 0.114 8 and 0.077 1,and the RE values were 14.01% and 7.81%,respectively,which showed that LWPLS algorithm was more accurate.Therefore,the LWPLS algorithm could improve the accuracy of quantitative model for Antai pill,exhibiting a wide generalization and application potential.
Key Words:local weighted partial least squares(LWPLS)  near infrared spectroscopy  partial least squares(PLS)  ferulic acid  senkyunolide A
引用本文:马力文,郭拓,马晋芳,史庆龙,肖环贤.基于局部加权偏最小二乘的近红外光谱分析方法研究[J].分析测试学报,2020,39(10):1254-1259.
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