Nonlinear Process Monitoring Based on Global Preserving Unsupervised Kernel Extreme Learning Machine

Nonlinear Process Monitoring Based on Global Preserving Unsupervised Kernel Extreme Learning Machine

Recently, the unsupervised extreme learning machine (UELM) technique as a nonlinear data mining approach has been employed to diagnose nonlinear process faults. However, during the dimensionality reduction of process observation data, UELM only aims at mining the local structure feature information...

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Bibliografische gegevens
Hoofdauteurs: Hanyuan Zhang, Xiaogang Deng, Yunchu Zhang, Chuanjing Hou, Chengdong Li, Zheng Xin
Formaat: Artikel
Taal:English
Gepubliceerd in: IEEE 2019-01-01
Reeks:IEEE Access
Onderwerpen:
Nonlinear process monitoring
unsupervised extreme learning machine
global structure analysis
kernel trick
support vector data description
Online toegang:https://ieeexplore.ieee.org/document/8781877/

Internet

https://ieeexplore.ieee.org/document/8781877/

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