Improved Process Monitoring Strategy Using Kantorovich Distance-Independent Component Analysis: An Application to Tennessee Eastman Process-Reference-Cited by-同舟云学术

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Improved Process Monitoring Strategy Using Kantorovich Distance-Independent Component Analysis: An Application to Tennessee Eastman Process

Published:2020 Issue: Volume:8 Page:205863-205877
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kini K. Ramakrishna^ORCID,Madakyaru Muddu^ORCID

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09257420.pdf?arnumber=9257420

Cited by 13 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. Mechanistic block‐based attention mechanism stacked autoencoder for describing typical unit connection industrial processes and their monitoring;The Canadian Journal of Chemical Engineering;2023-06-14

2. Faults prediction and monitoring of complex processes using an ensemble of machine learning regression models: application to the Tennessee Eastman Process;2023-06-09

3. Efficient Sitting Posture Recognition for Wheelchair Users: An Unsupervised Data-Driven Framework;IEEE Instrumentation & Measurement Magazine;2023-06

4. Farthest-Nearest Distance Neighborhood and Locality Projections Integrated With Bootstrap for Industrial Process Fault Diagnosis;IEEE Transactions on Industrial Informatics;2023-05

5. A Novel Two-Stage Fault-Detection Method Based on Constrained RVM and Integrating LDA With Minimax Probability Machine;IEEE Transactions on Industrial Informatics;2023-03

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