An Improved Bayesian-Based Wavelet Package Denoising Method for Data Reconciliation to Coking Chemical Process
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Qiang Ye | Kai Shen | Xingsheng Gu | Shengxi Wu | Xingsheng Gu | Kai Shen | Qiang Ye | Shengxi Wu
[1] Ruben Gonzalez,et al. Dynamic bayesian approach to gross error detection and compensation with application toward an oil sands process , 2012 .
[2] Wu Sheng-xi. Available estimation of measurement error variance/covariance and sequential compensating algorithm of gross error for data reconciliation , 2008 .
[3] Jules Thibault,et al. Autoassociative neural networks for robust dynamic data reconciliation , 2007 .
[4] Huihe Shao,et al. Theory Analysis of Nonlinear Data Reconciliation and Application to a Coking Plant , 2006 .
[5] Jules Thibault,et al. Dynamic data reconciliation: Alternative to Kalman filter , 2006 .
[6] L. Puigjaner,et al. Dynamic Data Reconciliation Based on Wavelet Trend Analysis , 2005 .
[7] Shankar Narasimhan,et al. Data reconciliation & gross error detection: an intelligent use of process data , 1999 .
[8] Jose A. Romagnoli,et al. Data Processing and Reconciliation for Chemical Process Operations , 1999 .
[9] B. Bakshi,et al. Multiscale rectification of random errors without fundamental process models , 1997 .
[10] C. M. Crowe,et al. Detecting persistent gross errors by sequential analysis of principal components , 1997 .
[11] Richard S.H. Mah,et al. Estimation of measurement error variances from process data , 1984 .