A remaining useful life prediction framework for aircraft engines that jointly addresses point estimation, uncertainty quantification, and the integration of aerospace risk preferences in safety-critical maintenance. The framework is evaluated on all four subsets of NASA's C-MAPSS benchmark datase
machine-learning aerospace predictive-maintenance conformal-prediction remaining-useful-life-prediction prognostics-and-health-management conformalized-quantile-regression
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Updated
Dec 23, 2025 - Python