NOUFERROUS METALLURGICAL EQUIPMENT

In order to accurately predict the original emission concentrations of SO2 and HCl acid gases from waste-to-energy incineration plants, a BP neural network prediction model for original concentrations of acid gas was established by using the Copula function to explore the magnitude of correlation between multiple operating parameters and acid gas emissions, and the parameters with greater correlation as input parameters for original concentration prediction were selected. The effectiveness of the above analysis method and prediction model is demonstrated by an example analysis with actual measured operational data of a waste incineration plant.