An Extreme Gradient Boosting Aided Fault Diagnosis Approach: A Case Study of Fuse Test Bench-Reference-Cited by-同舟云学术

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An Extreme Gradient Boosting Aided Fault Diagnosis Approach: A Case Study of Fuse Test Bench

Published:2022 Issue: Volume: Page:1-1
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Alfarizi Muhammad Gibran,Vatn Jrn,Yin Shen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/9184921/09750915.pdf?arnumber=9750915

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new dual-channel convolutional neural network and its application in rolling bearing fault diagnosis;Measurement Science and Technology;2024-06-27

2. Robust Electric Motor Fault Classification with Extra Trees Classifier on Comprehensive Dataset;2024 16th International Conference on Electronics, Computers and Artificial Intelligence (ECAI);2024-06-27

3. Activation Control Networks with Gradient Sparse Regularization for Mechanical Fault Diagnosis;2024 36th Chinese Control and Decision Conference (CCDC);2024-05-25

4. An XGBoost-assisted evolutionary algorithm for expensive multiobjective optimization problems;Information Sciences;2024-05

5. Enhancing Reliability Through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery;IEEE Access;2024

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