Wang, Kelong https://orcid.org/0009-0003-2664-2482
Guo, Bing https://orcid.org/0009-0007-8495-4897
Li, Nanyi
Funding for this research was provided by:
the Qinghai Provincial Department of Science and Technology Program (2021-ZJ-954Q)
the National Natural Science Foundation of China under the Youth Science Foundation Program (52005282)
Article Title: Highly accurate interpretable bearing fault diagnosis based on SHAP-RFE with Bayesian optimization support vector machines
Journal Title: Engineering Research Express
Article Type: paper
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Publication dates
Date Received: 2025-04-03
Date Accepted: 2025-09-02
Online publication date: 2025-09-16