Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks
arXiv 2610.06880v1•48a8d43bf2097cbc7d152ab051f583a733ffb546db39c0ef15dddff70905ea8b
Paper metadata
- arXiv ID
- 2610.06880
- Version
- v1
- Category
- cs.AI, cs.LG
- Authors
- Maikel Leyva-Vazquez, Dayron Rumbaut Rangel, Lorenzo Cevallos-Torres, Alexis Matheu Perez
- Publication date
- 2026-10-07T04:00:00Z
- Source identifier
- 2610.06880v1
- Public record ID
- record:sha256:48a8d43bf2097cbc7d152ab051f583a733ffb546db39c0ef15dddff70905ea8b
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Evidence and limitations
- Source ID
- arxiv_research
- Record identifier
- 48a8d43bf2097cbc7d152ab051f583a733ffb546db39c0ef15dddff70905ea8b
- Record type
- Source metadata
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