Prediction of NOx Concentration at Inlet Section of SCR Denitrification Reactor Based on Bidirectional Long Short-Term Memory Network and Least Squares Support Vector Machine Model

ZENG Wengen; CHEN Donglin; TANG Mingzhu; WANG Shuqi; HU Zhangmao

doi:10.12096/j.2096-4528.pgt.24008

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Prediction of NO_x Concentration at Inlet Section of SCR Denitrification Reactor Based on Bidirectional Long Short-Term Memory Network and Least Squares Support Vector Machine Model

Power Generation Technology Vol. 46, Issue 5, Pages: 996-1004(2025)

Power Generation and Environmental Protection|Updated：2026-06-29

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- Prediction of NO_x Concentration at Inlet Section of SCR Denitrification Reactor Based on Bidirectional Long Short-Term Memory Network and Least Squares Support Vector Machine Model
- “Experts have constructed a NOx concentration prediction model for the inlet section of SCR denitrification ammonia injection reactor, using BiLSTM for preliminary prediction and LSSVM for residual correction, providing a solution to the problems of dynamic adaptation delay and insufficient accuracy in ammonia injection control system.”
- Affiliations：
  School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, Hunan Province, China
- Author bio：
- Funds：
  National Natural Science Foundation of China(62173050)
- DOI：10.12096/j.2096-4528.pgt.24008
  CLC：
- Revised：2024-10-02，
- Accepted：
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Prediction of NO_x Concentration at Inlet Section of SCR Denitrification Reactor Based on Bidirectional Long Short-Term Memory Network and Least Squares Support Vector Machine Model

DOI：10.12096/j.2096-4528.pgt.24008

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