A Multiprocess Joint Modeling Method for Performance Prediction of Nonlinear Industrial Processes Based on Multitask Least Squares Support Vector Machine-Reference-Cited by-同舟云学术

A Multiprocess Joint Modeling Method for Performance Prediction of Nonlinear Industrial Processes Based on Multitask Least Squares Support Vector Machine

Published:2022-01-11 Issue:3 Volume:61 Page:1443-1452
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Chu Fei¹²^ORCID,Dai Bangwu³,Lu Ningyun⁴,Wang Fuli³,Ma Xiaoping¹²

Affiliation:

1. Artificial Intelligence Research Institute, China University of Mining and Technology, Xuzhou 221116, China

2. School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China

3. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China

4. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Funder

Fundamental Research Funds for the Central Universities

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.1c04075

Reference24 articles.

1. Condition-Driven Data Analytics and Monitoring for Wide-Range Nonstationary and Transient Continuous Processes

2. Batch Process Modeling and Monitoring With Local Outlier Factor

3. Bayesian Nonlinear Gaussian Mixture Regression and its Application to Virtual Sensing for Multimode Industrial Processes

4. Quality prediction for multi-grade processes by just-in-time latent variable modeling with integration of common and special features

5. Common Principal Components inkGroups

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