Prediction of FeO Content in Sintering Process Based on Heat Transfer Mechanism and Data-driven Model
Author:
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9326315/9326464/09327289.pdf?arnumber=9327289
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A Survey of Data-Driven Soft Sensing in Ironmaking System: Research Status and Opportunities;ACS Omega;2024-06-06
2. Application of deep learning in iron ore sintering process: a review;Journal of Iron and Steel Research International;2024-03-16
3. Multisource Information Fusion for Autoformer: Soft Sensor Modeling of FeO Content in Iron Ore Sintering Process;IEEE Transactions on Industrial Informatics;2023-12
4. Data‐driven modelling methods in sintering process: Current research status and perspectives;The Canadian Journal of Chemical Engineering;2022-12-29
5. Summarization of Sinter Quality Prediction Algorithms;2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2022-11-19
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