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...
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/161990 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |