Investigation On Model Of Acidogenic-Sulfate Reducing Bioreactor System With GANN

The niche of SRB is a key factor to the sulfate wastewater treatment in acidogenic-desulfate reactor. The restrictive ecological factors which affect the ability of sulfate-reducing of Sulfate Reducing Bacteria (SRB) in the acidogenic-desulfate reactor are COD/SO42-, pH, ALK, SO42-loading rate. A model and simulink on five factors (the four restrictive factors and time factor) has been built by using a new method that genetic algorithm neural network (GANN) in this paper. The model presents the realized niche and mechanism activity of SRB in the microbiological eco-system of the reactor. This work has been finished from the view of mathematical ecology. The GANN software which make the research of wastewater treatment with artificial intelligence and automatic controlling go ahead has been exploited based on Matlab programme,.By comparing the forecasting result of MCI and GANN in this paper, we can see that GANN have much more accuracy than MCI. GANN model has been built to predict the sulfate removal rate (η) resulting from the four factors that COD/SO₄^2-ratio (C/S), sulfate loading rate (Ns), pH and alkalinity (ALK). The simulation shows that it works well.Having ensured that the weihts of GANN is credible after being optimized, method of Partitioning Connection Weights (PCW) has been applied in this research to analyze the key factors at the different stages of microbial community ecological succession. The results of GANN model are consistent with that from prototype experiment as well as the microbial physiological and ecological laws. The multi-dimensional niche atlas of SRB is predicted, and the results show that the error is small between the calculation results and the real value. The model has the ability to realize the approximation and generalization between the ecological factors and the sulfate removal rate, to predict the treating degree of sulfate wastewater and to control the space factors during the treating process. The methods of this research have important significance for the optimization of operation and the stablity of equipment running in the sulfate waster water treatment area.