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Found 7 papers, 0 papers with code
Usage-Specific Survival Modeling Based on Operational Data and Neural Networks
The results also show that randomly resampling the dataset on each epoch is an effective way to reduce the size of the training data.
Neural Network-Based Piecewise Survival Models
In this paper, a family of neural network-based survival models is presented.
Structural Diagnosability Analysis of Switched and Modular Battery Packs
The findings indicate that the default sensor setup is insufficient for achieving complete fault isolability.
Analysis of Numerical Integration in RNN-Based Residuals for Fault Diagnosis of Dynamic Systems
Data-driven modeling and machine learning are widely used to model the behavior of dynamic systems.
Energy-Based Survival Models for Predictive Maintenance
Due to the complex behavior of system degradation, data-driven methods are often preferred, and neural network-based methods have been shown to perform particularly very well.
Time Series Fault Classification for Wave Propagation Systems with Sparse Fault Data
In this work Time Series Classification techniques are investigated, and especially their applicability in applications where there are significant differences between the individuals where data is collected, and the individuals where the classification is evaluated.
Massive Machine Type Communication Pilot-Hopping Sequence Detection Architectures Based on Non-Negative Least Squares for Grant-Free Random Access
The energy consumption is about 300 nJ/detection for the fast projected gradient algorithm using 256 iterations, leading to a convergence close to the theoretical.
