Supervised Attention-Based Bidirectional Long Short-Term Memory Network for Nonlinear Dynamic Soft Sensor Application-Reference-Cited by-同舟云学术

Supervised Attention-Based Bidirectional Long Short-Term Memory Network for Nonlinear Dynamic Soft Sensor Application

Published:2023-01-18 Issue:4 Volume:8 Page:4196-4208
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Yang Zeyu¹,Jia Ruining¹,Wang Peiliang¹^ORCID,Yao Le²,Shen Bingbing²

Affiliation:

1. Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou 313000, China

2. School of Mathematics, Hangzhou Normal University, Hangzhou 311121, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems

Natural Science Foundation of Huzhou

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c07400

Reference40 articles.

1. Locally Weighted Kernel Principal Component Regression Model for Soft Sensing of Nonlinear Time-Variant Processes

2. Deep Learning of Semisupervised Process Data With Hierarchical Extreme Learning Machine and Soft Sensor Application

3. A Survey on Deep Learning for Data-Driven Soft Sensors

4. Industrial Virtual Sensing for Big Process Data Based on Parallelized Nonlinear Variational Bayesian Factor Regression

5. Soft Sensor Modeling of Nonlinear Industrial Processes Based on Weighted Probabilistic Projection Regression

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