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
Power Generation and Environmental Protection|更新时间:2025-11-12
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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
“In the field of coal-fired unit denitrification, experts have constructed a NOx concentration prediction model for the inlet section of SCR denitrification ammonia injection reactor, effectively solving the problems of delayed dynamic adaptation of ammonia injection instructions and NOx concentration, and insufficient ammonia injection accuracy, providing accurate feedforward information for ammonia injection control system.”
Power Generation TechnologyVol. 46, Issue 5, Pages: 996-1004(2025)
作者机构:
长沙理工大学能源与动力工程学院,湖南省 长沙市 410114
作者简介:
基金信息:
National Natural Science Foundation of China(62173050)
ZENG Wengen,CHEN Donglin,TANG Mingzhu,et al.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[J].Power Generation Technology,2025,46(05):996-1004.
ZENG Wengen,CHEN Donglin,TANG Mingzhu,et al.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[J].Power Generation Technology,2025,46(05):996-1004. DOI: 10.12096/j.2096-4528.pgt.24008.
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