Application of machine learning-based models to understand and predict critical flux of oil-in-water emulsion in crossflow microfiltration

Random Forest (RF) and Neural Network (NN), respectively, were employed to understand and predict the critical flux (Jcrit) of oil-in-water emulsions in crossflow microfiltration. A total of 223 data sets from various studies were compiled, with nine operational parameters and one target variable of...

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Main Authors: Tanudjaja, Henry Jonathan, Chew, Jia Wei
其他作者: School of Chemical and Biomedical Engineering
格式: Article
語言:English
出版: 2022
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在線閱讀:https://hdl.handle.net/10356/161990
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