Quality Prediction Modeling for Industrial Processes Using Multiscale Attention-Based Convolutional Neural Network
Author:
Affiliation:
1. School of Automation, Central South University, Changsha, China
2. School of Engineering, Huzhou University, Huzhou, China
3. School of Information Science and Engineering, NingboTech University, Ningbo, China
Funder
Program of National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities of Central South University
CAAI-Huawei MindSpore Open Fund
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6221036/10500879/10465636.pdf?arnumber=10465636
Reference55 articles.
1. A Self-Interpretable Soft Sensor Based on Deep Learning and Multiple Attention Mechanism: From Data Selection to Sensor Modeling
2. Multirate Mixture Probability Principal Component Analysis for Process Monitoring in Multimode Processes
3. Multiscale Dynamic Feature Learning for Quality Prediction Based on Hierarchical Sequential Generative Network
4. Gated Stacked Target-Related Autoencoder: A Novel Deep Feature Extraction and Layerwise Ensemble Method for Industrial Soft Sensor Application
5. A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes
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