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A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples
Research article (Review of Scientific Instruments, 2023) · cited 11× · AI/ML
A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples
Summary
A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples is a scholarly article[1].
Key Facts
A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-novel-rolling-bearing-fault-diagnosis-method-based-on-parameter-optimization-variational-mode-decomposition-with-featu
MLA“A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-novel-rolling-bearing-fault-diagnosis-method-based-on-parameter-optimization-variational-mode-decomposition-with-featu.
BibTeX@misc{4ortxyz_a-novel-rolling-bearing-fault-diagnosis-method-based-on-parameter-optimization-variational-mode-decomposition-with-featu_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples}}, year = {2026}, url = {https://4ort.xyz/entity/a-novel-rolling-bearing-fault-diagnosis-method-based-on-parameter-optimization-variational-mode-decomposition-with-featu}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples — https://4ort.xyz/entity/a-novel-rolling-bearing-fault-diagnosis-method-based-on-parameter-optimization-variational-mode-decomposition-with-featu (retrieved 2026-05-24)