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Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization
DownloadFall 2015
Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a relatively new Bayesian approach to non-parametric data based modelling is investigated in detail. One of the primary...
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Fall 2020
Data-driven modeling approaches have been widely studied and applied to the process industries for inferential sensor development, process monitoring and fault detection and early warnings, etc. Essential information of process, like dynamic and relationships between process variables are buried...