Integrating transfer learning within data-driven soft sensor design to accelerate product quality control-Reference-Cited by-同舟云学术

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Integrating transfer learning within data-driven soft sensor design to accelerate product quality control

Published:2024-03 Issue: Volume:10 Page:100142
ISSN:2772-5081
Container-title:Digital Chemical Engineering
language:en
Short-container-title:Digital Chemical Engineering

Author:

Kay Sam,Kay Harry,Mowbray Max,Lane Amanda,Mendoza Cesar^ORCID,Martin Philip,Zhang Dongda^ORCID

Funder

EPSRC

Publisher

Elsevier BV

Reference31 articles.

1. A review of data-driven decision-making methods for industry 4.0 maintenance applications;Bousdekis;Electronics,2021

2. Chronéer, D., 2005. Product development in process industry–changes and consequences.

3. From model, signal to knowledge: a data-driven perspective of fault detection and diagnosis;Dai;IEEE Trans. Ind. Inform.,2013

4. Adversarial transferred data-assisted soft sensor for enhanced multigrade quality prediction;Dai;ACS Omega,2023

5. Comparison of physics-based and data-driven modelling techniques for dynamic optimisation of fed-batch bioprocesses;Del Rio-Chanona;Biotechnol. Bioeng.,2019

Cited by 1 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. Fault detection using machine learning based dynamic ICA-distributed CCA: Application to industrial chemical process;Digital Chemical Engineering;2024-06

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