Name
Abstract | ||
|---|---|---|
The warning of membrane fouling is of great important to maintain the stable operation of membrane bioreactor (MBR). However, traditional methods are so error-prone that probably do not acquire reliable solutions of membrane fouling due to its uncertainties. To overcome this problem, an intelligent warning method is proposed to monitor the status of MBR in this paper. The main advantages in this paper are as follows. First, an identification method, based on robust deep neural network (RDNN), is developed to diagnose the different types of membrane fouling. Second, a decision-making method, based on the restricted Boltzmann machine (RBM), is designed to distinguish the operational suggestion. Third, an intelligent warning system, based on the above two methods and some sensors, is developed to mitigate the membrane fouling in real wastewater treatment plants. Finally, the simulation and experimental results demonstrate the proposed warning method can obtain the higher identification accuracy of membrane fouling than other methods. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1007/s40815-021-01134-6 | INTERNATIONAL JOURNAL OF FUZZY SYSTEMS |
Keywords | DocType | Volume |
Membrane fouling, Uncertainties, Robust deep neural network, Decision-making, Warning system | Journal | 24 |
Issue | ISSN | Citations |
1 | 1562-2479 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao-Long Wu | 1 | 0 | 0.34 |
| Hong-Gui Han | 2 | 476 | 39.06 |
| Hui-Juan Zhang | 3 | 0 | 0.34 |
| Jun-Fei Qiao | 4 | 798 | 74.56 |