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A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction

Signal Processing 2022-03-24 v1 Machine Learning
Authors: Khouloud Abdelli , Helmut Griesser , Stephan Pachnicke
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Abstract

A hybrid prognostic model based on convolutional neural networks (CNN) and long short-term memory (LSTM) is proposed to predict the laser remaining useful life (RUL). The experimental results show that it outperforms the conventional methods.

Keywords

hybrid model cnn lstm remaining useful life laser prognostics

Cite

@article{arxiv.2203.12415,
  title  = {A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction},
  author = {Khouloud Abdelli and Helmut Griesser and Stephan Pachnicke},
  journal= {arXiv preprint arXiv:2203.12415},
  year   = {2022}
}

Comments

Optoelectronics and Communications Conference 2021

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