Developing Tensor-Based Common and Special Feature Analysis for Comprehensive Monitoring of Complex Batch Processes-Reference-Cited by-同舟云学术

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Developing Tensor-Based Common and Special Feature Analysis for Comprehensive Monitoring of Complex Batch Processes

Published:2022-07-11 Issue:28 Volume:61 Page:10156-10171
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Liu Jingxiang¹,Sun Deshun²,Xiao Yeliang³,Chen Junghui⁴^ORCID

Affiliation:

1. School of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, P. R. China

2. Southern University of Science and Technology Hospital, Intelligent Medical Innovation Center, Shenzhen, 518071, China

3. School of General Education, Dalian Neusoft University of Information, Dalian 116023, P. R. China

4. Department of Chemical Engineering, Chung-Yuan Christian University, Chung-Li District, Taoyuan 32023, Taiwan, R.O.C.

Funder

National Natural Science Foundation of China

Ministry of Science and Technology, Taiwan

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.2c00987

Reference37 articles.

1. Statistical monitoring of multistage, multiphase batch processes

2. Batch Process Modeling and Monitoring With Local Outlier Factor

3. Window-Based Stepwise Sequential Phase Partition for Nonlinear Batch Process Monitoring

4. Data-driven methods for batch data analysis – A critical overview and mapping on the complexity scale

5. Stationary Subspace Analysis-Based Hierarchical Model for Batch Processes Monitoring

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1. Few-shot learning on batch process modeling with imbalanced data;Chemical Engineering Science;2024-03

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