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A factorized-axis convolutional gated recurrent unit (GRU) that employs multiscale anisotropic convolution and dual-axis convolution block attention module to enhance directional features and highlight salient time-frequency regions is introduced.
A similarity matching (SM)‐based method that leverages historical time series patterns from analogous entities is introduced that outperformed 13 baseline models, including state‐of‐the‐art techniques, across two real‐world time series datasets.
Degradation process (DP) modeling is widely used for remaining useful life (RUL) prediction, particularly when run-to-failure data are limited. Neural networks can present complex degradation trajectories without prescribing a fixed degradation function; however, recursive health indicator (HI) forecasting is prone to...
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