A Deep Learning Approach for Process Data Visualization Using t-Distributed Stochastic Neighbor Embedding
Author:
Affiliation:
1. Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States
2. R&D Department, Shanghai SupeZET Engineering Technology Corp., Ltd, Shanghai, 200335, China
Funder
SupeZET Engineering Technology Co., Ltd
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.9b00975
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3. Topological preservation techniques for nonlinear process monitoring
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