兵工自动化2023，Vol.42Issue(12)：76-82,7.DOI:10.7690/bgzdh.2023.12.016
基于MI-PCA和ML-AE-ELM的脱硝系统入口NOx质量浓度预测
Prediction of NOx Mass Concentration at Inlet of Denitration System Based on MI-PCA and ML-AE-ELM
摘要
Abstract
In order to improve the prediction accuracy of nitrogen oxides(NOx)mass concentration at the inlet of denitration system,a combination algorithm prediction model of principal component analysis(PCA)and an extreme learning machine(ELM)with multi-layer self-coding structure based on mutual information is proposed.The selection of input variables is improved,and the network structure of the prediction algorithm is optimized by adding the historical NOx mass concentration.The experimental results show that compared with other prediction algorithm models,the proposed model has higher prediction efficiency and higher prediction accuracy under different working conditions,and shows good anti-noise ability and generalization ability.关键词
脱硝系统/NOx质量浓度/互信息/主成分分析/极限学习机/预测模型Key words
denitration system/NOx mass concentration/MI/PCA/ELM/prediction model分类
信息技术与安全科学引用本文复制引用
靳果,屈保中,朱清智..基于MI-PCA和ML-AE-ELM的脱硝系统入口NOx质量浓度预测[J].兵工自动化,2023,42(12):76-82,7.基金项目
河南省2021年科技发展计划(212102210527) （212102210527）
2022年度河南省高等学校重点科研项目(22A120004) （22A120004）
2020年南阳市科技计划项目(KJGG207) （KJGG207）
