ICP—AES分析的线性回归校准曲线

本文对ICP-AES分析中2种线性回归方法的校准曲线作了比较和讨论。对大多数元素而言,用加权法得到的校准曲线的斜率比不加权校准曲线的斜率略大,减小3校准曲线在低浓度部分的弯曲,曲线明显优于不加权校准曲线。将2种方法得到的校准曲线进行比较时,应将剩余标准偏差(或剩余变差平方和)及曲线截距等加以综合考虑。用含零标的标准系列制作校准曲线可使曲线的截距更接近原点,有利于提高在低浓度部分校准分析的准确性。     

聚乙烯熔体的离散松弛时间谱与熔融指数的关系

该文通过动态线性小振幅剪切震荡实验所得的聚乙烯熔体储能模量Ｇ′（ω）和耗能模量Ｇ″（ω）数据,采用最小二乘法线性回归、正则法和非线性回归法分别计算得到离散松弛时间谱,比较三种方法得到结果的差别,讨论计算参数、温度和材料对离散松驰时间谱影响．     

小波变换作为预处理的多元线性回归法

多元线性回归法是一种应用非常广泛的多变量分析方法，用于多组分同时定量分析。然而，噪声的存在影响了多元线性回归法分析的准确度。近年来小波变换以其多分辨率分析的特性、方法简单、快速等优点成为一种有效的去除分析信号噪声的方法。本实验就噪声对多元线性回归法的影响以及小波变换与多元线性回归法结合提高多元线性回归法分析准确性的有效性进行了研究。     

用线性回归与单纯形优化法研究配合物的组成

本文讨论了用线性回归和单纯形最优化法确定配合物实际组成的两种方法。这两种方法简单方便,既适用于水溶液也适用于非水溶液。     

比值导数光谱与多波长最小二乘回归分光光度法同时测定苯甲酸、苯甲醛和苯甲醇

提出了比值导数光谱多波长最小二乘回归分光光度法测定苯甲酸、苯甲醛和苯甲醇三组分混合物。合成试样４ 次平行测定的相对标准偏差为０ ．１６ ％ ～４．３５ ％ 。回收率在９１ ．４３ ％ ～１０５．９ ％ 之间。     

X-射线荧光光谱分析中偏最小二乘回归技术与基本参数法的研究

将偏最小二乘回归技术(PLS)与X-射线荧光分析中的基本参数法(FP)相结合,编制PLSFP软件,运用熔样技术,可以定量测定地质岩石样品中的十三个主,次量元素,并使准确度提高,模型预测能力增强。模型选择和最佳维数的确定方法是成功的关键。PLSFP软件采用结构化编程,由标准FORTRAN 77语言写成,可在UNIX,XENIX和DOS操作系统下运行。     

血清镁离子浓度与直肠癌患者谷氨酰转肽酶的关系

直肠癌患者血清镁离子(Mg²⁺)浓度对γ-谷氨酰转肽酶(γ-GT)的影响尚不明确,收集分析临床数据,Mg²⁺浓度不呈正态分布(D=0.737,P<0.05),按照中位数分组,比较不同组间临床病理特征的差异,用局部加权散点平滑(LOWESS)、分段线性回归方法,拟合血清Mg²⁺浓度与γ-GT的关系。结果发现,与Mg²⁺浓度小于0.92 mmol/L组的直肠癌患者比较,Mg²⁺浓度≥0.92 mmol/L组的γ-GT和血清总胆固醇较高(P均<0.05)。LOWESS的结果表明,原始数据中血清Mg²⁺浓度的两个变化点分别为0.92 mmol/L和0.99 mmol/L,自然对数转换的数据中血清Mg²⁺浓度的另外两个变化点分别为-0.167和-0.01。利用原始数据建立的两段线性回归模型表明,血清Mg²⁺浓度的变化点为0.98 mmol/L,Mg²⁺浓度<0.98 mmol/L对γ...     

基于主成分回归分析和偏最小二乘回归法的樱桃糖度检测的研究

选用烟台大樱桃为研究对象,采用便携式光谱仪对樱桃糖度进行检测,利用极差标准归一化方法和小波滤波,对其可见-近红外光谱数据进行预处理,分别运用主成分回归分析(PCR)法和偏最小二乘回归(PLSR)法建立了樱桃糖度定量分析模型,并对两种模型进行了比较。实验结果表明:在600~1 100nm波段范围内对樱桃糖度进行检测是可行的,并且PLSR模型的性能优于PCR模型。     

分光光度法同时测定两个干扰组份的研究 I.多波长数据线性回归法及其应用于同时测定微量锰和锌的探讨

In this paper, a linear regression method of multiwavelength data is proposed. The method, based on the difference of molar absorptivity between two coloured chelates at murti-wavelengths, can be applied to simultaneous spectrophotometric determination of two-interfering-component systems in the visible region. As an example, the availability as well as the optimum condition for simultaneous determination of Mn and Zn with 5-Br-PADAP in the presence of nonionic surfactant Triton X-100 have been studied. Measure the absorbance at 15 wavelengths over the range of 540-584 nm and treat the data with the suggested method, the linear correlation coefficients (γ) are found to be 0.998 in the synthetic mixtures containing microamounts of Mn and Zn with the concentration ratio from 1:10 to 10:1. The recoveries of both elements are 95-120% with the relative standard deviations (N=5) less than 17%. the method has been successfully used for direct determination of Mn and Zn in tap water. The new method proposed in this work is simple, fast and can be used for the analysis of two-interfering-component systems.     

Robust partial least squares regression: Part I,algorithmic developments

The work summarized in this paper presents the first part of a three‐paper series on robust partial least squares (RPLS) regression. Motivated by recent research activities in this area, this part provides a detailed algorithmic analysis of associated techniques, showing that existing work (i) may not represent a true robust formulation of partial least squares (PLS), (ii) may lead to convergence problems or (iii) may be insensitive to a certain type of outlier. On the basis of this analysis, Part I introduces a new conceptual RPLS algorithm that overcomes the deficiencies of existing work. The second part of this work details this new RPLS technique, compares its peformance with existing RPLS methods and provides an analysis on the computational efficiency and sensitivity of these algorithms. Whilst the first two parts of this work discuss algorithmic developments of RPLS, the final part concentrates on practical issues of RPLS implementations. This third part is devoted to practitioners of chemistry and chemical engineering covering a wide range of applications involving a calibration experiment, the analysis of recorded data from an industrial debutanizer process and data from a number of Raman spectroscopy experiments. Copyright © 2007 John Wiley & Sons, Ltd.     

基于最小角回归结合一元线性直接校正法的近红外光谱模型传递方法

针对近红外光谱分析技术中模型通用性较差的问题,提出了一种新的模型传递方法——最小角回归结合一元线性直接校正法(Least angle regression combined simple linear regression direct standardization,LARSLRDS)。该方法首先采用小波变换对样品光谱数据进行预处理,然后利用LAR实现样品全谱区光谱特征波长点的筛选,最后利用SLRDS对筛选出来的变量进行校正。采用汽油和药品样本的近红外光谱数据验证LAR-SLRDS性能,汽油数据集C7、C8、C9和C10成分的光谱差异为0. 002 8、0. 002 7、0. 002 6和0. 002 7,预测标准差为0. 410 6、0. 849 2、1. 034 9和1. 215 8;药品数据集活性、硬度和重量成分的光谱差异为0. 030 0、0. 031 8和0. 033 6,预测标准差为1. 933 8、0. 440 2和2. 130 9。结果表明,LAR-SLRDS算法不仅能够消除主、从仪器光谱之间存在的差异,实现模型传递,而且能够提高PLS定量模型的准确性和稳定性,具有广泛的应用潜力。     

线性回归间接极谱络合滴定

本文提出的方法是，根据一定的络合平衡和物料平衡，将间接极谱和线性回归应用于络合滴定，旨在扩大络合滴定的应用范围。文中对测定误差作了分析和计算，探讨了滴定点及权重选择问题。     

Precision limits and interval estimation in the calibration of 1-hydroxypyrene in urine and hexachlorbenzene in water,applying the regression triplet procedure on chromatographic data

A method for the determination of 1-hydroxypyrene in urine and hexachlorbenzene in water applying the regression triplet in the calibration procedure of chromatographic data has been applied. The detection limit and quantification limit are currently calculated on the basis of the standard deviation of replicate analyses at a single concentration. However, since the standard deviation depends on concentration, these single-concentration techniques result in limits that are directly dependent on spiking concentration. A more rigorous approach requires first careful attention to the three components of the regression triplet (data, model, method), examining (1) the data quality of the proposed model, (2) the model quality and (3) the least-squares method to be used for fulfilment of all least-squares assumptions. For high-performance liquid chromatography determination of 1-hydroxypyrene in urine and gas chromatography analysis of hexachlorbenzene in water, this paper describes the effects of deviations from five basic assumptions The paper considers the correction of deviations: identifying influential points, namely, outliers, the calibration task depends on the regression model used, and the least-squares method is based on the assumptions of the normality of the errors, homoscedasticity and the independence of errors. Results show that the approach developed provides improved estimates of analytical limits and that the single-concentration approaches currently in wide use are seriously flawed.     

Near-Infrared Spectroscopy Analytical Model Using Ensemble Partial Least Squares Regression

A novel ensemble-based feature selection method was developed which is designated as ensemble partial least squares regression coeffientents (EPRC). It was composed of two steps: generating a series of different single feature selectors and aggregating them to reach a consensus. Specifically, the bootstrap resampling approach was used to generate a diversity of single feature selectors, and the absolute values of the regression coefficients of the partial least squares (PLS) model were used to rank the features. Next, these feature rankings out of single feature selectors were aggregated by the weighted-sum approach. Finally, coupled with the regression model, the features selected by EPRC were evaluated through cross validation and an independent test set. By experiments of constructing the spectroscopy analysis model on three near infrared spectroscopy (NIRS) datasets, it was shown that the EPRC located key wavelengths, gave a promotion to regression performance, and was more stable and interpretable to the domain experts.     

Robust online algorithm for adaptive linear regression parameter estimation and prediction

In this article, we focus on adaptive linear regression methods and propose a new technique. The article begins with a review of the online passive aggressive algorithm (OPAA), an adaptive linear regression algorithm from the machine learning literature. We highlight the strengths and weaknesses of OPAA and compare it with other popular adaptive regression techniques such as moving window and recursive least squares, recursive partial least squares, and just‐in‐time or locally weighted regression. Modifications to OPAA are proposed to make it more robust and better suited for industrial soft‐sensor applications. The new algorithm is called smoothed passive aggressive algorithm (SPAA), and like OPAA, it follows a cautious parameter update strategy but is more robust. The trade‐off between SPAA's computation complexity and accuracy can be easily controlled by manipulating just two tuning parameters. We also demonstrate that the SPAA framework is quite flexible and a number of variants are easily formulated. Application of SPAA to estimate the time‐varying parameters of a numerically simulated autoregressive with exogenous terms (ARX) model and to predict the Reid vapor pressure of the bottoms flow from an industrial column demonstrates its superior performance over OPAA and comparable performance with the other popular algorithms. Copyright © 2016 John Wiley & Sons, Ltd.     

偏最小二乘法及主组分回归法用于药物组分的测定

本文研究了多元校准方法——偏最小二乘法(PLS)和主组份回归法(PCR)在药物多组份光度分析中的应用,获得了较满意的结果。而且在系列校准样品的实验设计、交叉证实法确定最佳因子数以及空缺组份体系的分析等方面进行了探讨。     

Regression models based on new local strategies for near infrared spectroscopic data

In this work, a comparative study of two novel algorithms to perform sample selection in local regression based on Partial Least Squares Regression (PLS) is presented. These methodologies were applied for Near Infrared Spectroscopy (NIRS) quantification of five major constituents in corn seeds and are compared and contrasted with global PLS calibrations. Validation results show a significant improvement in the prediction quality when local models implemented by the proposed algorithms are applied to large data bases.     

激光拉曼光谱解谱和处理的方法研究

研究一种拉曼光谱解谱和处理的方法。以化学计量学为基础,信号处理技术为工具,配合计算机算法的数据处理方法。具体为基线校正:对拉曼光谱原始信号进行基于自适应迭代重加权惩罚最小二乘法的基线校正;平滑:对进行完基线校正的拉曼光谱信号进行基于惩罚最小二乘法的平滑;峰检测:对进行完基线校正和平滑的信号进行基于连续小波变换的峰检测。这种基于惩罚最小二乘法的光谱平滑具有快速,可以连续控制平滑度并且可以进行交叉验证得到最客观的平滑值。改善了基于非对称最小二乘法的传统基线校正方法的两个缺陷。同时,基于连续小波变换的峰检测算法可以自动地并且同时考虑峰形和峰高对峰进行检测,最大限度地降低了峰检测假阳性的概率。