Online Adaptive Modeling Framework for Deep Belief Network-Based Quality Prediction in Industrial Processes
Author:
Affiliation:
1. School of Automation, Central South University, Changsha, 410083 Hunan, China
2. PengCheng Laboratory, Shenzhen 518066, China
3. School of Engineering, Huzhou University, Huzhou 313000, China
Funder
Ministry of Science and Technology of the People's Republic of China
National Natural Science Foundation of China
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.1c02768
Reference40 articles.
1. Online Quality Prediction of Industrial Terephthalic Acid Hydropurification Process Using Modified Regularized Slow-Feature Analysis
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4. A New Soft-Sensor-Based Process Monitoring Scheme Incorporating Infrequent KPI Measurements
5. Quality variable prediction for chemical processes based on semisupervised Dirichlet process mixture of Gaussians
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