Application of MBR Membrane Flux Prediction Based on Elman Neural Network

Abstract

In the field of MBR sewage treatment, membrane fouling affects the performance of MBR process. The direct consequence of it is the decline in membrane flux. The prediction of MBR flux is of great significance to the application of MBR. Because the neural network can arbitrarily approximate any continuous function with arbitrary precision, and it can establish a complex nonlinear relationship between input and output model, it is widely used in the field of prediction. We use a feedback type Elman neural network to model the MBR membrane flux, and use this model to predict membrane flux and evaluate the degree of membrane fouling. The results show that the prediction results of membrane flux obtained by Elman neural network prediction model are higher than BP neural network model. The prediction model has a guiding effect on the design and application of MBR system. 1