Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 3SAGD
- 2Optimization
- 1Chance Constrained Model Predictive Control
- 1Data Mining
- 1EM algorithm
- 1Gaussian process regression
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Spring 2017
Model Predictive Control (MPC) is widely applied in the process industry nowadays. Chemical processes are corrupted by all kinds of uncertainties, such as measurement noises, disturbances and parameter uncertainties. Without consideration of uncertainties, conventional MPC will cause various...
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Spring 2018
Steam-assisted gravity drainage (SAGD) is an enhanced oil recovery (EOR) technology widely used in Canada. Data available in SAGD industrial processes contain valuable information for monitoring, soft sensing, control, and optimization. This thesis focuses on data mining and optimization in the...
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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...