Online prediction of quality‐related variables for batch processes using a sequential phase partition method-Reference-Cited by-同舟云学术

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Online prediction of quality‐related variables for batch processes using a sequential phase partition method

Published:2019-04-05 Issue:9 Volume:97 Page:2483-2497
ISSN:0008-4034
Container-title:The Canadian Journal of Chemical Engineering
language:en
Short-container-title:Can. J. Chem. Eng.

Author:

Li Zheng¹²³⁴,Wang Pu¹²³⁴,Gao Xuejin¹²³⁴,Qi Yongsheng⁵,Chang Peng¹²³⁴

Affiliation:

1. Faculty of Information TechnologyBeijing University of Technology Beijing 100124 China

2. Engineering Research Centre of Digital CommunityMinistry of Education Beijing 100124 China

3. Beijing Laboratory for Urban Mass Transit Beijing 100124 China

4. Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 China

5. School of Electric PowerInner Mongolia University of Technology Hohhot 010051 China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Beijing Municipal Commission of Education

Publisher

Wiley

Subject

General Chemical Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cjce.23494

Reference39 articles.

1. Latent variable based concurrent multi-trends analysis method for monitoring batch processes with irregular and limited batches

2. On-line quality prediction of batch processes using a new kernel multiway partial least squares method

3. Joint-Individual Monitoring of Parallel-Running Batch Processes Based on MCCA

4. Covariance-oriented qualitative and quantitative calibration analysis for multistage batch processes

5. Quality prediction and analysis for large-scale processes based on multi-level principal component modeling strategy

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1. An improved transfer learning approach based on geodesic flow kernel for multiphase batch process soft sensor modeling;Transactions of the Institute of Measurement and Control;2024-02-16

2. Phase partition and KPI ‐related process monitoring for batch processes using a novel canonical correlation analysis strategy;The Canadian Journal of Chemical Engineering;2022-09-27

3. Multihorizons transfer strategy for continuous online prediction of time‐series data in complex systems;International Journal of Intelligent Systems;2022-04-28

4. Fermentation process quality prediction using teacher student stacked sparse recurrent autoencoder;The Canadian Journal of Chemical Engineering;2021-09-20

5. Soft Sensor Framework Based on Semisupervised Just-in-Time Relevance Vector Regression for Multiphase Batch Processes with Unlabeled Data;Industrial & Engineering Chemistry Research;2020-10-22

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