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Permanent link (DOI): https://doi.org/10.7939/R33R0Q25C

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Processability Analysis using Principal Component Analysis and Support Vector Machine Open Access

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Other title
Subject/Keyword
Process Analysis
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhang,Yixin
Supervisor and department
Zhao,Qing (ECE) Xu,Zhenghe (CME)
Examining committee member and department
Prasad,Vinay(CME)
Xu,Zhenghe (CME)
Reformat,Marek(ECE)
Zhao,Qing (ECE)
Department
Department of Electrical and Computer Engineering
Specialization
Control Systems
Date accepted
2014-01-21T10:15:10Z
Graduation date
2014-06
Degree
Master of Science
Degree level
Master's
Abstract
The obtained model developed outperforms the existing linear and logistic prediction methods in terms of content prediction error. As the proof of concept, the methodology is applied to an oil sands processing dataset created using an artificial model with such variables as bitumen content and fines content of ores, along with the processing variables such as pH and temperature.
Language
English
DOI
doi:10.7939/R33R0Q25C
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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