[WP-D] Poster Session 2

[WP-D-2] An Interpretable Graph Neural Network Approach for Laser Lifetime Prediction

○Yizheng Zuo^1,2,3, Ye Zhu^1,2,3, Yi Lai^1,2,3, Qing Lan^1,2,3, Xuwen Liang^1,2,3 (1.University of Chinese Academy of Sciences, 2.Innovation Academy for Microsatellites of CAS, 3.Key Laboratory for Satellite Digitalization Technology of CAS)

Keywords:

Semiconductor lasers

This paper proposes an interpretable model based on an attention mechanism and graph convolutional neural network (GCN) for predicting the mean-time-to-failure (MTTF) of lasers, enhancing interpretability while outperforming traditional methods.