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Flash point prediction of ternary miscible organic mixtures using random forest regression | Synapse
March 3, 2026
Flash point prediction of ternary miscible organic mixtures using random forest regression
SS
Shuangyu Song
XS
Xiaoya Song
Key Points
The model successfully predicts flash points for ternary mixtures with high accuracy, reinforcing the reliability of the method.
Key evidence shows a predictive accuracy exceeding 90% when applying random forest algorithms on diverse mixtures.
Assessment using random forest regression demonstrates effective prediction capabilities for ternary miscible organic mixtures.
This highlights the importance of reliable flash point predictions for safety in handling organic solvents.
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Song et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75ea2c6e9836116a296fb
https://doi.org/https://doi.org/10.1016/j.jlp.2026.105927