An artificial intelligence modeling framework based on microbial community structure prediction enhances the pollutant removal efficiency of the algae-bacteria granular sludge system.

A two-stage optimal control model for the ABGS system, which includes prediction of microbial community structure and planning of pollutant removal efficiency is constructed, which enabled intelligent optimization of the system's pollutant removal efficiency through the regulation of operational parameters.