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Asphaltene Stability Prediction via ML by Sauban Ahmed is a document available to read on EtoBox.
What is Asphaltene Stability Prediction via ML about?
The document discusses using machine learning algorithms to predict asphaltene stability in crude oils based on SARA values. It tested linear discriminant analysis, linear regression, decision trees, and random forests on a dataset of 95 crude oil samples. The models achieved 60-80% accuracy. Resins were found to be the most important parameter. The moderate accuracy suggests SARA alone is not enough to reliably determine stability.
- Author
- Sauban Ahmed
- Language
- EN