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From Shallow to Deep:A Novel Correlation Network Representation Regression Framework for Modeling and Monitoring MIQ-Driven Blast Furnace Ironmaking Processes

Siwei Lou Chunjie Yang Zhe Liu Hanwen Zhang Chao Liu Ping Wu

自动化学报（英文版）2026，Vol.13Issue(2)：281-299,19.

自动化学报（英文版）2026，Vol.13Issue(2)：281-299,19.DOI:10.1109/JAS.2025.125765

From Shallow to Deep:A Novel Correlation Network Representation Regression Framework for Modeling and Monitoring MIQ-Driven Blast Furnace Ironmaking Processes

Siwei Lou ¹Chunjie Yang ¹Zhe Liu ²Hanwen Zhang ³Chao Liu ⁴Ping Wu⁵

作者信息

1. State Key Laboratory of Industrial Control Technology(SKLICT),Zhejiang University,Hangzhou 310027,China
2. State Key Laboratory of Industrial Control Technology(SKLICT),Zhejiang University,Hangzhou 310027,China||State Key Laboratory of Metallurgical Intelligent Manufacturing System,Beijing 100071,China
3. School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China
4. Guangxi Liuzhou Iron and Steel Group Co.,Ltd.,Liuzhou
5. 545002,China 5School of Information Science and Engineering,Zhejiang Sci-Tech University,Hangzhou 310018,China
折叠

摘要

关键词

Canonical correlation analysis(CCA)/ironmaking process(IP)/molten iron quality(MIQ)/neural network(NN)/pro-cess monitoring

Key words

Canonical correlation analysis(CCA)/ironmaking process(IP)/molten iron quality(MIQ)/neural network(NN)/pro-cess monitoring

引用本文复制引用

Siwei Lou,Chunjie Yang,Zhe Liu,Hanwen Zhang,Chao Liu,Ping Wu..From Shallow to Deep:A Novel Correlation Network Representation Regression Framework for Modeling and Monitoring MIQ-Driven Blast Furnace Ironmaking Processes[J].自动化学报（英文版）,2026,13(2):281-299,19.

基金项目

This work was supported in part by the Pioneer Research and Development Program of Zhejiang(2025C01021),Zhejiang Province Postdoctoral Research Project Selection Fund(ZJ2025061),the National Science and Technology Major Project-Intelligent Manufacturing Systems and Robotics of China(2025ZD1602000,2025ZD1601800),the National Natural Science Foundation of China(61933015,62273030,62573387),the Natural Science Foundation of Zhejiang province,China(LY24F030004),and the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y). （2025C01021）

自动化学报（英文版）

ISSN：2329-9266

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