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Skip to Search Results- 3Data Reconciliation
- 2Gross Error Detection
- 1Bayesian Inference
- 1Bayesian Network
- 1Causal Inference
- 1Data Rectification
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Fall 2010
Data reconciliation and gross error detection are traditional methods toward detecting mass balance inconsistency within process instrument data. These methods use a static approach for statistical evaluation. This thesis is concerned with using an alternative statistical approach (Bayesian...
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Probabilistic Graphical Models for Data Reconciliation and Causal Inference in Process Data Analytics
DownloadSpring 2021
Data reconciliation methods play an important role in minimizing the measurement error and gross error that are present in the process data with respect to the process model. On the other hand, causal analysis helps in determining the relationship among the process variables from the data. It is...
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Simultaneous Gross Error Detection and Data Reconciliation Using Gaussian Mixture Distribution
DownloadFall 2017
The intensive competitive nature of the world market, the growing significance of quality products, and the increasing importance and the number of safety and environmental issues and regulations, respectively, have increased the need for fast and low-cost changes in chemical processes to enhance...