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Predicting multi-component oil viscosity using machine learning methods

delete2026-07-11
delete0
PRE
AI
V
Vladimir I. Deshchenya *
N
Nikolay Kondratyuk
A
Anna P. Sivakova
O
Oleg Sushkov
D
Dmitry Kozhevnikov
V
Vladimir Petrov
T
Timur Aliev
A
Anton A. Muravev
M
Michael G. Medvedev
E
Ekaterina V. Skorb
DOI：10.1016/j.ces.2026.124616delete
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摘要

摘要

En 中文
• 强鲁棒性粘度模型可训练于小型匿名专有数据集。• 梯度提升算法实现16.2%的中位误差，优于基于物理的模型。• Walther方程筛选复杂粘度数据集中的实验离群值。
Keyword:
Kinematic viscosity
Lubricating oils
Machine learning
Materials science

期刊

Chemical Engineering Science 封面图
Chemical Engineering Science
IF:
4.3
论文数:
2.3W
被引数:
5.5W

机构

M
moscow institute of physics and technology
学者数:
181
论文数: 72
被引数: 0
I
itmo university
学者数:
836
论文数: 291
被引数: 0
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