An Integrated Ensemble Learning Model for Imbalanced Fault Diagnostics and Prognostics

An Integrated Ensemble Learning Model for Imbalanced Fault Diagnostics and Prognostics

With the development of artificial intelligence technology, data-driven fault diagnostics and prognostics in industrial systems have been a hot research area since the large volume of industrial data is being collected from the industrial process. However, imbalanced distributions exist pervasively...

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Bibliographic Details
Main Authors: Zhenyu Wu, Wenfang Lin, Yang Ji
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Industrial prognostics
class-imbalance learning
machine learning
ensemble learning
Online Access:https://ieeexplore.ieee.org/document/8295035/

Internet

https://ieeexplore.ieee.org/document/8295035/

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