Research

Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks

Single source1 source7 Oct 2026

arXiv:2610.06880v1 Announce Type: cross Abstract: Machine learning classifiers for bearing fault detection produce scalar confidence scores that conflate confident errors with genuinely ambiguous predictions, and the conventional truth/falsity pair (F = 1 - T)

Reported by 1 source

arxiv.orghttps://arxiv.org/abs/2610.06880

← Back to all developments · Signals are a development reported by more than one source. See the methodology.

Research

Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks

Single source1 source7 Oct 2026

Reported by 1 source

arxiv.orghttps://arxiv.org/abs/2610.06880

← Back to all developments · Signals are a development reported by more than one source. See the methodology.