Application of Improved BP Neural Network Based on LM Algorithm in Desulfurization System of Thermal Power Plant

被引：0
|
作者：
Cheng, Huanxin [1 ]
Cui, Lijie [1 ]
Li, Jing [1 ]
机构：
[1] Qing Dao Univ Sci & Technol, Sch Automat & Elect Engn, Qing Dao, Peoples R China
来源：
2017 CHINESE AUTOMATION CONGRESS (CAC) | 2017年
关键词：
flue gas wet desulphurization; improved BP neural network; LM algorithm; desulfurization efficiency;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Use flue gas wet desulphurization technology to reduce the emissions of sulfur dioxide. The improved BP neural network model based on LM algorithm was established according to the factors that influence sulfur dioxide emissions, and the network weights and threshold value were adjusted repeatedly. The real data obtained from thermal power plants are simulated and verified. The results show that the improved BP network prediction model of LM algorithm has higher prediction accuracy of desulfurization efficiency, and has certain guiding significance for field operation.
引用
收藏
页码：5917 / 5920
页数：4
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