Noisy parallel hybrid model of NBGRU and NCNN architectures for remaining useful life estimation
Author:
Affiliation:
1. Electrical and Computer Engineering, Concordia University, Montreal, Canada;
2. Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Canada
Publisher
Informa UK Limited
Subject
Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality
Link
https://www.tandfonline.com/doi/pdf/10.1080/08982112.2020.1754427
Reference35 articles.
1. Adaptive composite filters for pattern recognition in nonoverlapping scenes using noisy training images
2. A multimodal and hybrid deep neural network model for Remaining Useful Life estimation
3. NBLSTM: Noisy and Hybrid Convolutional Neural Network and BLSTM-Based Deep Architecture for Remaining Useful Life Estimation
4. Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process
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