The continuous development of artificial intelligence technology has impacted quantitative analysis flue gas
desulfurization(FGD)system in various factors,and has created favorable condition for its desulfurization efficiency and
economic cost. By analyzing the details of the network construction and parameter selection in FGD system SO2 emission
prediction calculated by neural network algorithm,the application characteristics of the algorithm in FGD system is
discussed. In addition,targeted discuss is made on the optimization of booster fan,oxidation fan and syrup circulation
pump,which aims at refining the detailed design and optimization targets of the prediction + optimization algorithm in FGD
systems.