国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Aiming at the problem of low prediction accuracy of NOx concentration at the outlet of selective Catalytic Reduction (SCR) denitrification system in thermal power plants, a prediction model of NOx concentration at the outlet of denitrification system in thermal power plant based on Empirical Mode Decomposition (EMD) and Support Vector Machine for Regression (SVR) was proposed.Firstly, the empirical mode decomposition (EMD) algorithm was used to decompose the data series of NOx concentration at the outlet of denitrification system in thermal power plants, and a finite number of intrinsic mode functions (IMF) were obtained at different time scales. Then, the SVR algorithm was used to model and predict the decomposition data of NOx concentration. Finally, the prediction results of all IMFs were added up. The sum is used as the final predictor of the concentration of NOx at the outlet.By comparing the proposed EMD-SVR with standard SVR, BP, ELM, EMD-BP and EMD-ELM models, the results showed that the prediction accuracy based on EMD-SVR model was higher. Compared with the real values, the directional statistics (Dstat), mean absolute percentage error (MAPE) and root mean square error (RMSE) were 0.914, 1.51% and 0.346 mg/Nm3,respectively.