Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring-Reference-Cited by-同舟云学术

Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring

Published:2019-05-22 Issue:23 Volume:58 Page:9952-9958
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Yan Shifu¹,Yan Xuefeng¹^ORCID

Affiliation:

1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China

Funder

Ministry of Education 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.9b01325

Reference27 articles.

1. Survey on data-driven industrial process monitoring and diagnosis

2. Review of Recent Research on Data-Based Process Monitoring

3. Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008-2017

4. Data-Based Techniques Focused on Modern Industry: An Overview

5. Fault-relevant Principal Component Analysis (FPCA) method for multivariate statistical modeling and process monitoring

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