基于先进的混合机器学习建模,用于预测不同温度下离子液体的特性

Saud Bawazeer1

  • 1Department of Pharmaceutical Sciences, College of Pharmacy, Umm Al-Qura University, P.O. Box 751, Makkah, Saudi Arabia. ssbawazeer@uqu.edu.sa.

Scientific reports
|July 2, 2025
PubMed
概括

机器学习模型准确地预测了离子液体的表面张力,从而降低了实验成本. 额外树木 (ET) 在绿色化学应用中表现出高精度和低错误率的卓越性能.

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