Apr 3, 2023 · A new bearing RUL prediction method based on the federated learning (FL) and Taylor-expansion network pruning, namely, RUL-FLTNP, is proposed in this article.
In Chen et al. (2023) , a new bearing RUL prediction approach based on federated learning (FL) and Taylor-expansion network pruning is proposed. The model used ...
Therefore, this paper proposes a bearing RUL prediction method using the FL with Taylor-expansion network pruning criterion, named RUL-FLTNP. In this method, a ...
This paper presents a new method to predict the RUL of engineering systems using network pruning and rebirth within the FL framework.
Bearing Remaining Useful Life Prediction Using Federated Learning With Taylor Expansion Network Pruning ; Interval Estimation of Landslide Displacement Predictio ...
In Chen et al. (2023) , a new bearing RUL prediction approach based on federated learning (FL) and Taylor-expansion network pruning is proposed. The model used ...
Nov 1, 2023 · A dynamic weighted federated RUL prediction framework is proposed in this paper, which consists of a cloud server and multiple edge clients.
Federated learning with network pruning and rebirth for remaining useful life prediction of engineering systems. https://doi.org/10.1016/j.mfglet.2023.08.
Missing: Taylor- Expansion
Bearing remaining useful life prediction using federated learning with Taylor-expansion network pruning. X Chen, H Wang, S Lu, R Yan. IEEE Transactions on ...
Oct 14, 2024 · This study presents a multi-channel multi-scale deep learning approach. Initially, an improved Savitzky‒Golay filter (ISG) addresses challenges posed by large ...
Missing: Taylor- Expansion