Recursive Wavelength-Selection Strategy to Update Near-Infrared Spectroscopy Model with an Industrial Application
暂无分享,去创建一个
Biao Huang | Haitao Zhang | Swanand Khare | Enbo Feng | Mulang Chen | Eric Lau | S. Khare | Biao Huang | M. Chen | Enbo Feng | Haitao Zhang | Eric Lau
[1] K. Helland,et al. Recursive algorithm for partial least squares regression , 1992 .
[2] Li Yan-kun,et al. Determination of diesel cetane number by consensus modeling based on uninformative variable elimination , 2012 .
[3] Bhupinder S. Dayal,et al. Improved PLS algorithms , 1997 .
[4] Julian Morris,et al. Process analytical technologies and real time process control a review of some spectroscopic issues and challenges , 2011 .
[5] C. Jun,et al. Performance of some variable selection methods when multicollinearity is present , 2005 .
[6] R. Yu,et al. Systematic prediction error correction: a novel strategy for maintaining the predictive abilities of multivariate calibration models. , 2011, The Analyst.
[7] Ping Wu,et al. Online dual updating with recursive PLS model and its application in predicting crystal size of purified terephthalic acid (PTA) process , 2006 .
[8] R. Barnes,et al. Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra , 1989 .
[9] D. Massart,et al. Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.
[10] Xue-song Liu,et al. NIR spectroscopy as a process analytical technology (PAT) tool for on-line and real-time monitoring of an extraction process , 2012 .
[11] J. Roger,et al. Robustness of models developed by multivariate calibration. Part II: The influence of pre-processing methods , 2005 .
[12] H. Martens,et al. Light scattering and light absorbance separated by extended multiplicative signal correction. application to near-infrared transmission analysis of powder mixtures. , 2003, Analytical chemistry.
[13] S. Qin. Recursive PLS algorithms for adaptive data modeling , 1998 .
[14] Hongdong Li,et al. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. , 2009, Analytica chimica acta.
[15] Kevin M. Higgins,et al. Updating a near-infrared multivariate calibration model formed with lab-prepared pharmaceutical tablet types to new tablet types in full production. , 2012, Journal of pharmaceutical and biomedical analysis.
[16] Jean-Michel Roger,et al. Dynamic orthogonal projection. A new method to maintain the on-line robustness of multivariate calibrations. Application to NIR-based monitoring of wine fermentations , 2006 .
[17] A. Savitzky,et al. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .
[18] S. Engelsen,et al. Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .
[19] Jordi Coello,et al. NIR calibration in non-linear systems: different PLS approaches and artificial neural networks , 2000 .
[20] R. Yu,et al. Quantitative spectroscopic analysis of heterogeneous mixtures: the correction of multiplicative effects caused by variations in physical properties of samples. , 2012, Analytical chemistry.
[21] Lutgarde M. C. Buydens,et al. Improvement of PLS model transferability by robust wavelength selection , 1998 .
[22] E. Martin,et al. Gaussian process regression for multivariate spectroscopic calibration , 2007 .
[23] Beata Walczak,et al. Selection and weighting of samples in multivariate regression model updating , 2005 .
[24] Onno E. de Noord,et al. Multivariate calibration standardization , 1994 .
[25] J. Roger,et al. Application of LS-SVM to non-linear phenomena in NIR spectroscopy: development of a robust and portable sensor for acidity prediction in grapes , 2004 .
[26] R. Yu,et al. Maintaining the predictive abilities of multivariate calibration models by spectral space transformation. , 2011, Analytica chimica acta.
[28] Bruce R. Kowalski,et al. Weighting schemes for updating regression models—a theoretical approach , 1999 .
[29] Zou Xiaobo,et al. Variables selection methods in near-infrared spectroscopy. , 2010, Analytica chimica acta.
[30] A Garrido-Varo,et al. Non-linear regression methods in NIRS quantitative analysis. , 2007, Talanta.
[31] Charles R. Hurburgh,et al. A Tutorial on Near Infrared Spectroscopy and Its Calibration , 2010 .
[32] Frans van den Berg,et al. Review of the most common pre-processing techniques for near-infrared spectra , 2009 .
[33] Roman M. Balabin,et al. Comparison of linear and nonlinear calibration models based on near infrared (NIR) spectroscopy data for gasoline properties prediction , 2007 .
[34] Jani Kaartinen,et al. Optical spectrum based measurement of flotation slurry contents , 2008 .
[35] D. B. Funk,et al. Noise Robustness Comparison for near Infrared Prediction Models , 2011 .
[36] Bing Xu,et al. NIR analysis for batch process of ethanol precipitation coupled with a new calibration model updating strategy. , 2012, Analytica chimica acta.
[37] R. Leardi,et al. Genetic algorithms applied to feature selection in PLS regression: how and when to use them , 1998 .
[38] Qingsong Xu,et al. Elastic Net Grouping Variable Selection Combined with Partial Least Squares Regression (EN-PLSR) for the Analysis of Strongly Multi-Collinear Spectroscopic Data , 2011, Applied spectroscopy.
[39] Limin Fang,et al. Application of near infrared spectroscopy for rapid analysis of intermediates of Tanreqing injection. , 2010, Journal of pharmaceutical and biomedical analysis.
[40] D. Massart,et al. Standardization of near-infrared spectrometric instruments , 1996 .
[41] Julian Morris,et al. Improving the linearity of spectroscopic data subjected to fluctuations in external variables by the extended loading space standardization. , 2008, The Analyst.
[42] Yukihiro Ozaki,et al. Improvement of partial least squares models for in vitro and in vivo glucose quantifications by using near-infrared spectroscopy and searching combination moving window partial least squares , 2006 .
[43] S. Wold,et al. Orthogonal signal correction of near-infrared spectra , 1998 .
[44] M. C. U. Araújo,et al. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis , 2001 .
[45] H. Hyötyniemi,et al. Recursive multimodel partial least squares estimation of mineral flotation slurry contents using optical reflectance spectra. , 2009, Analytica chimica acta.
[46] Bhupinder S. Dayal,et al. Recursive exponentially weighted PLS and its applications to adaptive control and prediction , 1997 .
[47] Manabu Kano,et al. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection. , 2011, International journal of pharmaceutics.
[48] Roman M. Balabin,et al. Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data. , 2011, Analytica chimica acta.