A Metric-Driven Evaluation Framework for Remaining Useful Life Prognosis with Quantified Uncertainty. [PDF]
Vashishtha G, Chauhan S, Ertarğın M.
europepmc +1 more source
Prediction of aero engine remaining service life using a bidirectional GRU model with self attention mechanism. [PDF]
Fu W +7 more
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Turbofan Engine Remaining Useful Life Prediction with Reliable Prediction Intervals via LSTM-Based Quantile Regression and Conformal Calibration. [PDF]
Diao R, Zhou M, Meng G, Wang S.
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Risk-sensitive joint inventory-maintenance strategy for bearing health management under prognostic uncertainty: an uncertainty-aware deep reinforcement learning approach. [PDF]
Zhang Z, Shen N, Wang X.
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Data-Driven Health Prognostics of NMC Lithium-Ion Batteries via Impedance Spectroscopy Using a Hybrid CNN-BiLSTM Model. [PDF]
Liu Z +5 more
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A novel dual-dimensional contrastive self-supervised learning-based framework for rolling bearing remaining useful life prediction. [PDF]
Shen Z +5 more
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A two-stage framework for cost-sensitive predictive maintenance using deep learning, GANs, and risk-aware clustering. [PDF]
Hakami A.
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Remaining useful life prediction method based on gated dilation causal convolution. [PDF]
He J, Sun W, Zhang C.
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Genetic Algorithm-Optimized CNN-BiLSTM Framework for Predicting the Remaining Useful Life of IGBT Modules. [PDF]
Hao Y +5 more
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A sparrow search algorithm-optimized LSTM framework with EMD denoising for rolling element bearing remaining useful life prediction. [PDF]
Li Q, Zhang B, Fang X.
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