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

arXiv: https://arxiv.org/abs/2203.12415 · HTML: https://mlsanity.com/paper/2203.12415/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 4 references that are in the map.
- First posted on arXiv 19 Mar 2022.

## Built on by (most cited first, 2 of 2)

- [A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication](https://mlsanity.com/paper/2211.02842/) (2022)
- [Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder](https://mlsanity.com/paper/2211.02847/) (2022)

## Abstract (arXiv)

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.