Prior knowledge-augmented unsupervised shapelet learning for unknown abnormal working condition discovery in industrial process
X Wan, L Cen, X Chen, Y Xie, W Gui - Advanced Engineering Informatics, 2024 - Elsevier
Unknown abnormal working condition discovery is the key of refinement industrial
production. Clustering industrial time series is an effective way to discover unknown working …
production. Clustering industrial time series is an effective way to discover unknown working …
PKG-DTSFLN: Process Knowledge-guided Deep Temporal–spatial Feature Learning Network for anode effects identification
W Yue, J Chai, X Wan, Y Xie, X Chen, W Gui - Journal of Process Control, 2024 - Elsevier
In the aluminum electrolysis process, the accurate identification of anode effect (AE) can
improve production efficiency. However, the existing methods fail to effectively capture the …
improve production efficiency. However, the existing methods fail to effectively capture the …
Multi-criteria decision-making based on the combination of interval-valued hesitant fuzzy information and ORESTE method
J Li, L Niu, Q Chen, Z Wang - 2024 - researchsquare.com
As an important extension of hesitant fuzzy sets, interval-valued hesitant fuzzy sets (IVHFSs)
show the flexibility of decision makers (DMs) in expressing hesitant information. Accordingly …
show the flexibility of decision makers (DMs) in expressing hesitant information. Accordingly …