Modeling of Integrated Processes for Coking Flue Gas Desulfurization and Denitrification Based on RBFNN

This paper proposes an efficient modeling method based on the history running data of a coking chemical company flue gas desulfurization and denitrification integration device: construct data set according to the technology principle and corresponding data preprocessing method; make division of working conditions and reduce the sample set by means of K-Means clustering method; realize static modeling for each of the conditions based on RBF neural network The simulation results show the effectiveness of the method and the artificial neural network model.