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 |
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Other Authors: | School of Chemical and Biomedical Engineering |
Format: | Article |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/161990 |
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Institution: | Nanyang Technological University |
Language: | English |
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