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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.

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Results for "Probability Distributions on a Circle"

Supervisors: Li, Zukui (Department of Chemical and Materials Engineering)

  • Process Data Rectification and Process Optimization with Uncertainty

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    Fall 2017

    Yuan, Yuan

    reconcile the data. Among various approaches for optimization with uncertainty, chance constraint problem is a natural way to quantify the reliability of the solutions by setting a restriction on the level of the probability that the constraints are satisfied. In the case that multiple constraints should be

    satisfied simultaneously, joint chance constraint is appropriate to model the uncertainties. However, joint chance constraint problem is generally intractable and a variety of methods are available to approximate it into tractable forms. Robust optimization with the distribution-free property is an approach

    models. This thesis develops a novel robust optimization framework to consider the uncertain nonlinear optimization problems. The thesis provides practical applications as well. An economic optimization problem is investigated for steam generation and water distribution for SAGD (steam-assisted-gravity

  • Machine learning-based monitoring of complex reactive systems

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    Spring 2022

    Puliyanda, Anjana Thimmaiah

    from the reactant to the product configurations. A self-supervised 3D convolutional neural network autoencoder is trained to extract features from the reactant and product simulation trajectories, the probability distributions across the difference between which is used to assess if the solvent

    Processing of complex feedstocks for the production of value-added chemicals and fuels is industrially important. The lack of a priori knowledge of the innumerable species and the reaction pathways governing their conversion, has posed challenges to monitoring these processes. Although, data-driven

    models have been used, their lack of interpretability and an end-to-end modeling framework has limited the efficiency of diagnostic decisions in process monitoring. On the other hand, systems where the mechanistic knowledge of the species and their reactions are arrived at from first-principles

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