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Machine learning refinery sensor data to predict catalyst saturation levels

Bram Steurtewagen (UGent) and Dirk Van den Poel (UGent)
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Keywords
General Chemical Engineering, Computer Science Applications, Data mining, Machine learning, Catalytic cracking, SOFT SENSOR, PERFORMANCE, SIMULATION

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Please use this url to cite or link to this publication:

MLA
Steurtewagen, Bram, and Dirk Van den Poel. “Machine Learning Refinery Sensor Data to Predict Catalyst Saturation Levels.” COMPUTERS & CHEMICAL ENGINEERING, vol. 134, 2020, doi:10.1016/j.compchemeng.2020.106722.
APA
Steurtewagen, B., & Van den Poel, D. (2020). Machine learning refinery sensor data to predict catalyst saturation levels. COMPUTERS & CHEMICAL ENGINEERING, 134. https://doi.org/10.1016/j.compchemeng.2020.106722
Chicago author-date
Steurtewagen, Bram, and Dirk Van den Poel. 2020. “Machine Learning Refinery Sensor Data to Predict Catalyst Saturation Levels.” COMPUTERS & CHEMICAL ENGINEERING 134. https://doi.org/10.1016/j.compchemeng.2020.106722.
Chicago author-date (all authors)
Steurtewagen, Bram, and Dirk Van den Poel. 2020. “Machine Learning Refinery Sensor Data to Predict Catalyst Saturation Levels.” COMPUTERS & CHEMICAL ENGINEERING 134. doi:10.1016/j.compchemeng.2020.106722.
Vancouver
1.
Steurtewagen B, Van den Poel D. Machine learning refinery sensor data to predict catalyst saturation levels. COMPUTERS & CHEMICAL ENGINEERING. 2020;134.
IEEE
[1]
B. Steurtewagen and D. Van den Poel, “Machine learning refinery sensor data to predict catalyst saturation levels,” COMPUTERS & CHEMICAL ENGINEERING, vol. 134, 2020.
@article{8661084,
  articleno    = {106722},
  author       = {Steurtewagen, Bram and Van den Poel, Dirk},
  issn         = {0098-1354},
  journal      = {COMPUTERS & CHEMICAL ENGINEERING},
  keywords     = {General Chemical Engineering,Computer Science Applications,Data mining,Machine learning,Catalytic cracking,SOFT SENSOR,PERFORMANCE,SIMULATION},
  language     = {eng},
  pages        = {8},
  title        = {Machine learning refinery sensor data to predict catalyst saturation levels},
  url          = {http://dx.doi.org/10.1016/j.compchemeng.2020.106722},
  volume       = {134},
  year         = {2020},
}

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