Adversarial smoothing tri-regression for robust semi-supervised industrial soft sensor-Reference-Cited by-同舟云学术

Adversarial smoothing tri-regression for robust semi-supervised industrial soft sensor

Published:2021-12 Issue: Volume:108 Page:86-97
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Feng Liangjun,Zhao Chunhui^ORCID,Huang Biao^ORCID

Funder

State Key Laboratory of Industrial Control Technology

National Natural Science Foundation of China

Zhejiang University

China National Funds for Distinguished Young Scientists

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering

Reference30 articles.

1. Development of a variable selection method for soft sensor using artificial neural network and nonnegative garrote;Sun;J. Process Control,2014

2. Multichannel diffusion graph convolutional network for the prediction of endpoint composition in the converter steelmaking process;Feng;IEEE Trans. Instrum. Meas.,2021

3. Mode-cloud data analytics based transfer learning for soft sensor of manufacturing industry with incremental learning ability;Wang;Control Eng. Pract.,2020

4. Dual attention based encoder–decoder: a customized sequence to sequence learning for soft sensor development;Feng;IEEE Trans. Neural Netw. Learn. Syst.,2020

5. Quality prediction based on phase-specific average trajectory for batch processes;Zhao;AIChE J.,2010

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