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VIBRATIONAL SPECTROSCOPY

Characterization of a Stable Adaptive Calibration Model Using Near-Infrared Spectroscopy and Partial Least Squares with a Kalman Filter

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Pages 1176-1193 | Received 13 Jul 2017, Accepted 24 Aug 2017, Published online: 23 Feb 2018

References

  • Aguilera, A. M., M. Escabias, C. Preda, and G. Saporta. 2010. Using basis expansions for estimating functional PLS regression. Chemometrics and Intelligent Laboratory Systems 104:289–305. doi:10.1016/j.chemolab.2010.09.007
  • Ahmadi, A., D. Han, M. Karamouz, and R. Remesan. 2009. Input data selection for solar radiation estimation. Hydrological Processes 23:2754–64.
  • ASTM E1655. 2012. Standard practices for infrared multi-variate quantitative analysis. West Conshohocken: ASTM International.
  • Chu, X. 2011. Molecular spectroscopy analytical technology combined with chemometrics and its applications. Beijing: Chemical Industry Press.
  • Dayal, B. S., and J. F. MacGregor. 1997. Recursive exponentially weighted PLS and its applications to adaptive control and prediction. Journal of Process Control 7:169–79.
  • Deng, Z. L. 2001. Kalman filtering and wiener filtering-modern time series analysis method. Harbin: Institute of Technology Press.
  • Fitzgerald, R. 1971. Divergence of the Kalman filter. IEEE Transactions on Automatic Control 16:736–47.
  • Gao, Y., and J. Q. Zhang. 2007. Kalman filter with wavelet-based unknown measurement noise estimation and its application for information fusion. Acta Electronica Sinica 35:108–11.
  • Helland, K., H. E. Berntsen, O. S. Borgen, and H. Martens. 1992. Recursive algorithm for partial least squares regression. Chemometrics and Intelligent Laboratory Systems 14:129–37.
  • Iturrarán-Viveros, U. 2012. Smooth regression to estimate effective porosity using seismic attributes. Journal of Applied Geophysics 76:1–12.
  • Li, H., J. X. Wang, Z. N. Xing, and G. Shen. 2011. Influence of improved Kennard/Stone algorithm on the calibration transfer in near-infrared spectroscopy. Guang Pu Xue Yu Guang Pu Fen Xi 31:362–65.
  • Li, T., J. Hou, and L. Yao. 2014. Kalman artificial neural network with measurable noise estimation by gamma test for dynamic industrial process modeling. Journal of Mechanical Engineering 50:29–35.
  • Li, X. Y., X. F. Wang, W. Wang, and J. Zhang. 2007. Estimation of apple storage quality properties based on the mechanical properties with BP neural network. Transactions from the Chinese Society of Agricultural Engineering 23:150–53.
  • Liang, Y. Z., and Q. S. Xu. 2012. Instrumental analysis of complex systems-white, grey and black analytical systems and their multivariate methods. Beijing: Chemical Industry Press.
  • Lu, B., I. Castillo, L. Chiang, and T. F. Edgar. 2014. Industrial PLS model variable selection using moving window variable importance in projection. Chemometrics and Intelligent Laboratory Systems 135:90–109.
  • Luo, L., S. Bao, J. Mao, and D. Tang. 2016. Quality prediction and quality-relevant monitoring with multilinear PLS for batch processes. Chemometrics and Intelligent Laboratory Systems 150:9–22.
  • Ma, M. Y., G. Y. Wang, A. M. Huang, Z. Y. Zhang, Y. H. Xiang, and X. Gu. 2012. Study on artificial neural network combined with near infrared spectroscopy for wood species identification. Guang Pu Xue Yu Guang Pu Fen Xi 32:2377–81.
  • Mei, Q. P., T. F. Li, L. Z. Yao, D. Huang, and Y. L. Yang. 2016. Study of an adaptable calibration model of near-infrared spectra based on KF-PLS. Chemometrics and Intelligent Laboratory Systems 157:152–61.
  • Moore, A. 1991. Efficient memory-based learning for robot control. PhD. thesis, University of Cambridge, Cambridge: Computer Laboratory. [Technical Report No. 209].
  • Negiz, A., and A. Çinar. 1997. PLS, balanced, and canonical variate realization techniques for identifying VARMA models in state space. Chemometrics and Intelligent Laboratory Systems 38:209–21.
  • Ni, W., S. D. Brown, and R. Man. 2014. A localized adaptive soft sensor for dynamic system modeling. Chemical Engineering Science 111:350–63.
  • Simoglou, A., E. B. Martin, and A. J. Morris. 1999. Dynamic multivariate statistical process control using partial least squares and canonical variate analysis. Computers & Chemical Engineering 23:S277–80.
  • Song, J., C. L. Li, G. Y. Xing, Q. F. Meng, J. H. Lu, J. M. Cao, Y. L. Zhou, D. Wang, and L. Teng. 2014. Study on analyzing active ingredient of Marasmius androsaceus via radial basis function neural network combining with near infrared spectroscopy. Acta Optica Sinica 34:1–6.
  • Sorjamaa, A., J. Hao, N. Reyhani, Y. Ji, and A. Lendasse. 2007. Methodology for long-term prediction of time series. Neurocomputing 70:2861–69.
  • Standardization Administration of the People’s Republic of China. 2006. Water quality-determination of the chemical oxygen demand-dichromate method, GB-11914-1989. Beijing: Standardization Administration of the People’s Republic of China.
  • Standardization Administration of the People’s Republic of China. 2014. Standard guidelines for molecular spectroscopy multivariate calibration quantitative analysis, GB/T 29859–2013. Beijing, China: Standardization Administration of the People’s Republic of China.
  • Stefánsson, A., N. Končar, and A. J. Jones. 1997. A note on the Gamma test. Neural Computing and Applications 5:131–33.
  • Teppola, P., S. P. Mujunen, and P. Minkkinen. 1999. Kalman filter for updating the coefficients of regression models. A case study from an activated sludge waste-water treatment plant. Chemometrics and Intelligent Laboratory Systems 45:371–84.
  • Wei, K. L., M. Chen, Z. Y. Wen, and Y. K. Xie. 2014. Research on signal processing for water quality monitoring based on continuous spectral analysis. Guang Pu Xue Yu Guang Pu Fen Xi 34:3368–73.
  • Yu, R. Q. 1991. Introduction to chemometrics. Changsha: Hunan Education Press.
  • Zhao, F. C., C. Y. Yin, and L. Zhang. 2008. Wavelet-transformation based unscented Kalman filter and its application. Radio Communication Technology 34:46–48.

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