Abstract：To study the measurement delay of NOx emission concentration of coal-fired boilers in power stations, a prediction model of NOx emission concentration of coal-fired boilers in power stations based on mutual information (MI) and long short-term memory neural network (LSTM) was proposed. Firstly, the delay time between the candidate input variable and the output variable NOx concentration was calculated using mutual information, and the MRMR algorithm was introduced to screen out the optimal feature subset, and the optimal feature subset was used as the input of LSTM model. The prediction model of NOx emission concentration of boiler is established. The simulation results show that the root mean square error (RMSE) and mean absolute error (MAE) of the proposed model are 4.626mg/m3 and 3.836mg/m3, respectively. Compared with the LSTM model without variable selection and delay consideration, the prediction accuracy is significantly improved.
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2023, Vol. 44 
