Reliable Soft Sensors With an Inherent Process Graph Constraint-Reference-Cited by-同舟云学术

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Reliable Soft Sensors With an Inherent Process Graph Constraint

Published:2024-06 Issue:6 Volume:20 Page:8798-8806
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Zhai Ruikun¹^ORCID,Zheng Junhua²^ORCID,Song Zhihuan¹^ORCID,Ge Zhiqiang³^ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China

2. School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou, China

3. Peng Cheng Laboratory, Shenzhen, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10550081/10480138.pdf?arnumber=10480138

Reference25 articles.

1. A Survey on Deep Learning for Data-Driven Soft Sensors

2. GraSSNet: Graph Soft Sensing Neural Networks

3. Review of Recent Research on Data-Based Process Monitoring

4. Nonlinear Dynamic Soft Sensor Modeling With Supervised Long Short-Term Memory Network

5. A Faster Dynamic Feature Extractor and Its Application to Industrial Quality Prediction

Cited by 2 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. Multi-view graph convolutional network with comprehensive structural learning: Enhancing dynamics representation for industrial processes;Journal of Process Control;2024-11

2. Temporal graph convolutional network soft sensor for molecular weight distribution prediction;Chemometrics and Intelligent Laboratory Systems;2024-09

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