Research of BP Neural Network Based on GA-WOA Algorithm Optimization in MBR Membrane Pollution Simulation

Abstract

For the membrane fouling problem faced by the MBR (Membrane Bio-Reactor) system, an intelligent model is constructed to predict the membrane fouling. The BP neural network has strong self-learning, self-adaptive and generalization capabilities and is widely used in the prediction of MBR membrane pollution, but membrane fouling is a complex dynamic process, which is difficult to simulate accurately by classical mathematical models. Aiming at this problem, the GA-WOA hybrid algorithm was introduced to optimize the BP neural network, and the MBR membrane fouling prediction model was constructed. The simulation results show that the BP neural network model optimized by GA-WOA hybrid algorithm is more suitable and accurate than that optimized by whale optimization algorithm in predicting MBR membrane fouling.