Prediction of Thermogravimetric Data for Asphaltenes Extracted from Deasphalted Oil Using Machine Learning Techniques
Kaushik Sivaramakrishnan,
Joy H. Tannous,
Vignesh Chandrasekaran
Abstract:Thermogravimetric analysis (TGA)
has been extensively used in the
bitumen literature to investigate its thermal stability and various
stages of thermal decomposition. The primary aim of these studies
has been to calculate the kinetic parameters, such as activation energy
and the pre-exponential factor of each thermal event. However, in
our current paper, we explore the application of three machine learning
(ML) techniques, namely, support vector regression (SVR), random forest
(RF), and gradient booster regres… Show more
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