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Effectively predicting the remaining useful life (RUL) of a product is significant for reasonable reliability planning and maintenance activities. The long-short term memory (LSTM) model, which belongs to deep learning methods, was applied for RUL prediction of turbine engines, and a parameter optimization method with Bayesian theory was studied.

RUL Prediction by LSTM Model with Bayesian Parameter Optimization for Turbine Engines