A Novel Decentralized Weighted ReliefF-PCA Method for Fault Detection

A Novel Decentralized Weighted ReliefF-PCA Method for Fault Detection

The decentralized weighted ReliefF-PCA (DWRPCA) method is proposed to improve the performance of principal component analysis (PCA) for fault detection. The improved ReliefF-PCA algorithm is used to select the principal components instead of the traditional cumulative percent variance (CPV) criterio...

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Bibliographic Details
Main Authors: Yinghua Yang, Xiangming Chen, Yue Zhang, Xiaozhi Liu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Fault detection
ReliefF algorithm
decentralized weighted model
principal component analysis
Bayesian information criterion
Online Access:https://ieeexplore.ieee.org/document/8846019/

Internet

https://ieeexplore.ieee.org/document/8846019/

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