Simulation and Dynamic Properties Analysis of the Anaerobic–Anoxic–Oxic Process in a Wastewater Treatment PLANT Based on Koopman Operator and Deep Learning

The accurate simulation of the dynamics anaerobic–anoxic–oxic (A2O) process in biochemical reactions wastewater treatment plants (WWTPs) is important for system prediction and optimization. Previous studies have used real-time monitoring data WWTPs to develop data-driven predictive models, but these models cannot be provide mathematical analysis A2O dynamic properties. In this study, we developed a new method determining using deep learning Koopman operator address above problems. This was validated through from real-world WWTP east China compared it with traditional model. According results, achieved high-accuracy prediction. Meanwhile, help operator, able analyze asymptotical stability convergence behavior process, which provides brand-new perspective in-depth study reactor dynamics.