A Multiobjective Particle Swarm Optimizer based Localized Feature Selection for Imbalanced Fault Diagnosis-Reference-Cited by-同舟云学术

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A Multiobjective Particle Swarm Optimizer based Localized Feature Selection for Imbalanced Fault Diagnosis

Published:2024-06-30 Issue: Volume:14 Page:1-8
ISSN:
Container-title:2024 IEEE Congress on Evolutionary Computation (CEC)
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Author:

Gao Lin¹,Zhou Yu¹,Guo Hainan²,Wu Kwong Sam Tak³

Affiliation:

1. College of Computer Science and Software Engineering, Shenzhen University,Shenzhen,Guangdong,China

2. College of Management, Shenzhen University,Shenzhen,Guangdong,China

3. Lingnan University,Department of Computing and Decision Sciences,Hong Kong,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609966/10611750/10612211.pdf?arnumber=10612211

Reference30 articles.

1. A Systematic Review on Imbalanced Learning Methods in Intelligent Fault Diagnosis

2. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

3. Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives

4. Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions

5. A sequential resampling approach for imbalanced batch process fault detection in semiconductor manufacturing

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