A Bayesian Learning Approach to Modeling Pseudoreaction Networks for Complex Reacting Systems: Application to the Mild Visbreaking of Bitumen

A data-mining and Bayesian learning approach is used to model the reaction network of a low-temperature (150–400 °C) visbreaking process for field upgrading of oil sands bitumen. Obtaining mechanistic and kinetic descriptions for the chemistry involved in this process is a significant challenge beca...

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Veröffentlicht in:	Industrial & engineering chemistry research 2017-03, Vol.56 (8), p.1961-1970
Hauptverfasser:	Tefera, Dereje Tamiru, Yañez Jaramillo, Lina Maria, Ranjan, Rajesh, Li, Chaoqun, de Klerk, Arno, Prasad, Vinay
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Aliphatic compounds Bayesian analysis Bitumens Data mining Machine learning Mathematical models Networks
Online-Zugang:	Volltext
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