Just‐in‐time learning for the prediction of oil sands ore characteristics using GPS data in mining applications-Reference-Cited by-同舟云学术

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Just‐in‐time learning for the prediction of oil sands ore characteristics using GPS data in mining applications

Published:2020-04-04 Issue:10 Volume:98 Page:2125-2136
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can J Chem Eng

Author:

Magbool Jan Nabil¹^ORCID,Huang Biao¹,Espejo Aris²,Zelmer Luke³,Xu Fangwei²,Gulbransen Lee⁴

Affiliation:

1. Department of Chemical & Materials Engineering, University of Alberta Edmonton Alberta Canada

2. Process Control and Automation Syncrude Canada Limited Fort McMurray Alberta Canada

3. Operations Support Mining Syncrude Canada Limited Fort McMurray Alberta Canada

4. Regulatory and Lease Development Syncrude Canada Limited Fort McMurray Alberta Canada

Publisher

Wiley

Subject

General Chemical Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjce.23742

Reference23 articles.

1. Processability of Oil Sand Ores in Alberta

2. Image processing for the oil sands mining industry [In the Spotlight]

3. P.Dougan K.McDowell presented at IEEE Industry Applications Society Dynamic Modeling Control Applications for Industry Workshop Vancouver May1997.

4. Oil Sand Slurry Conditioning Tests in a 100 mm Pipeline Loop

5. Processibility of Athabasca Oil Sand Using a Laboratory Hyd ro t ransport Extraction System (LHES)

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1. A mutual information-based Variational Autoencoder for robust JIT soft sensing with abnormal observations;Chemometrics and Intelligent Laboratory Systems;2020-09

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