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There are 7576616 results for: content related to: Detection of gross errors in process data

  1. Bayesian method for simultaneous gross error detection and data reconciliation

    AIChE Journal

    Volume 61, Issue 10, October 2015, Pages: 3232–3248, Yuan Yuan, Shima Khatibisepehr, Biao Huang and Zukui Li

    Version of Record online : 23 MAY 2015, DOI: 10.1002/aic.14864

  2. Performance studies of the measurement test for detection of gross errors in process data

    AIChE Journal

    Volume 31, Issue 7, July 1985, Pages: 1187–1201, C. Iordache, R. S. H. Mah and A. C. Tamhane

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690310717

  3. Generalized likelihood ratio method for gross error identification

    AIChE Journal

    Volume 33, Issue 9, September 1987, Pages: 1514–1521, S. Narasimhan and R. S. H. Mah

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690330911

  4. Generalized likelihood ratios for gross error identification in dynamic processes

    AIChE Journal

    Volume 34, Issue 8, August 1988, Pages: 1321–1331, Shankar Narasimhan and Richard S. H. Mah

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690340810

  5. Maximum likelihood data rectification: Steady-state systems

    AIChE Journal

    Volume 41, Issue 11, November 1995, Pages: 2415–2426, Lloyd P. M. Johnston and Mark A. Kramer

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690411108

  6. On the definition of software accuracy in redundant measurement systems

    AIChE Journal

    Volume 51, Issue 4, April 2005, Pages: 1201–1206, Miguel J. Bagajewicz

    Version of Record online : 3 MAR 2005, DOI: 10.1002/aic.10379

  7. Gross error detection and data reconciliation in steam-metering systems

    AIChE Journal

    Volume 32, Issue 5, May 1986, Pages: 733–742, R. W. Serth and W. A. Heenan

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690320503

  8. Estimating state probability distributions from noisy and corrupted data

    AIChE Journal

    Volume 44, Issue 3, March 1998, Pages: 591–602, Lloyd P. M. Johnston and Mark A. Kramer

    Version of Record online : 16 APR 2004, DOI: 10.1002/aic.690440310

  9. Detecting persistent gross errors by sequential analysis of principal components

    AIChE Journal

    Volume 43, Issue 5, May 1997, Pages: 1242–1249, Hongwei Tong and Cameron M. Crowe

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690430513

  10. Data reconciliation and gross-error detection for dynamic systems

    AIChE Journal

    Volume 42, Issue 10, October 1996, Pages: 2841–2856, João S. Albuquerque and Lorenz T. Biegler

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690421014

  11. Downside financial loss of sensor networks in the presence of gross errors

    AIChE Journal

    Volume 52, Issue 11, November 2006, Pages: 3825–3841, Duy Quang NguyenThanh, Kitipat Siemanond and M. Bagajewicz

    Version of Record online : 14 SEP 2006, DOI: 10.1002/aic.10992

  12. Review of Real Time Optimization in the Chemical Process Industries

    Developments in Chemical Engineering and Mineral Processing

    Volume 3, Issue 2, 1995, Pages: 67–87, M. R. Naysmith and P. L. Douglas

    Version of Record online : 15 MAY 2008, DOI: 10.1002/apj.5500030202

  13. Detection of gross erros in data reconciliation by principal component analysis

    AIChE Journal

    Volume 41, Issue 7, July 1995, Pages: 1712–1722, Hongwei Tong and Cameron M. Crowe

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690410711

  14. Rectification of multiscale data with application to life cycle inventories

    AIChE Journal

    Volume 53, Issue 4, April 2007, Pages: 876–890, Heui-Seok Yi and Bhavik R. Bakshi

    Version of Record online : 26 FEB 2007, DOI: 10.1002/aic.11119

  15. Enhancing Life-Cycle Inventories via Reconciliation with the Laws of Thermodynamics

    Journal of Industrial Ecology

    Volume 11, Issue 4, October 2007, Pages: 5–25, Jorge L. Hau, Heui-seok Yi and Bhavik R. Bakshi

    Version of Record online : 8 FEB 2008, DOI: 10.1162/jiec.2007.1165

  16. Objective quality control of observations using Bayesian methods. Theory, and a practical implementation

    Quarterly Journal of the Royal Meteorological Society

    Volume 114, Issue 480, January 1988 Part B, Pages: 515–543, A. C. Lorenc and O. Hammon

    Version of Record online : 15 DEC 2006, DOI: 10.1002/qj.49711448012

  17. Introduction and Motivation

    Robust Statistics: The Approach Based on Influence Functions

    Frank R. Hampel, Elvezio M. Ronchetti, Peter J. Rousseeuw, Werner A. Stahel, Pages: 1–77, 2011

    Published Online : 14 OCT 2011, DOI: 10.1002/9781118186435.ch1

  18. Maximum power tests for gross error detection using likelihood ratios

    AIChE Journal

    Volume 36, Issue 10, October 1990, Pages: 1589–1591, Shankar Narasimhan

    Version of Record online : 17 JUN 2004, DOI: 10.1002/aic.690361017

  19. On the use of a Huber norm for observation quality control in the ECMWF 4D-Var

    Quarterly Journal of the Royal Meteorological Society

    Volume 141, Issue 690, July 2015 Part A, Pages: 1514–1527, Christina Tavolato and Lars Isaksen

    Version of Record online : 31 OCT 2014, DOI: 10.1002/qj.2440

  20. The maximum-power test for gross errors in the original constraints in data reconciliation

    The Canadian Journal of Chemical Engineering

    Volume 70, Issue 5, October 1992, Pages: 1030–1036, Cameron M. Crowe

    Version of Record online : 27 MAR 2009, DOI: 10.1002/cjce.5450700527