20180927_Prediction of membrane fouling using artificial neural networks for wastewater...

1. Title, Journal and Authors

Title: Prediction of membrane fouling using artificial neural networks for wastewater treated by membrane bioreactor technologies: bottlenecks and possibilities


Journal: Environmental Science Pollution Research

Authors: Félix Schmitt1,2 Khac-Uan Do1

1 School of Environmental Science and Technology, Hanoi University of Science and Technology, Hanoi, Vietnam

2 Energy and Environmental Department, National Institute of Applied Sciences of Lyon, 69621 Villeurbanne Cedex, France


2. Summary

Felix Schmitt and Khac-Uan Do reviewed prediction methods for membrane fouling using ANN in wastewater treatment (WWT) process. Many numerical methods based on the physical and chemical theory were developed to predict membrane-fouling mechanism in WWT process. There complexity and non-linearity made it hard to predict trend and value of fouling. However, ANNs construct model based on the monitoring data. It builds model by training step. Therefore, ANNs seems to be suitable for fouling prediction in WWT process. Although a few research was conducted to develop the ANNs based on the pilot plant data, they showed good results for membrane fouling prediction.


3. Originality & Creativity

 - They summarized characteristic of WWT process and explained advantages of ANNs as a prediction algorithm.


4. Application to research



5. Contact

Seung Ji Lim (Ph.D. Student)

Environmental Systems Engineering Lab.

School of Earth Sciences and Environmental Engineering

Gwangju Institute of Science and Technology

1 Oryong-dong Buk-gu Gwangju, 500-712, Korea

 Phone : +82-10-7935-8845

E-mail : fblsj90@gist.ac.kr


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