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Predicting multi-component oil viscosity using machine learning methods
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AI
DOI：10.1016/j.ces.2026.124616.png)
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Abstract
En 中文
• Robust viscosity models are trainable on small, anonymized proprietary datasets. • Gradient boosting achieves 16.2% median error, outperforming physics-based models. • Walther equation screens experimental outliers in complex viscosity datasets.
Keywords:
Kinematic viscosity
Lubricating oils
Machine learning
Materials science
Journal
IF:
4.3
Papers:
2.3W
Citations:
5.5W
Organization
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