A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction
arXiv:2203.12415v17 citationsh-index: 30
Originality Synthesis-oriented
AI Analysis
This addresses laser maintenance prediction for engineering applications, but it appears incremental as it combines existing methods.
The paper tackled the problem of predicting laser remaining useful life (RUL) by proposing a hybrid CNN-LSTM model, and the result was that it outperformed conventional methods, though no concrete numbers were provided.
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.