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Found 4 papers, 0 papers with code
Towards a Probabilistic Fusion Approach for Robust Battery Prognostics
The combination of Neural Networks, Bayesian modelling concepts and ensemble learning strategies, form a valuable prognostics framework to combine uncertainty in a robust and accurate manner.
Uncertainty Distribution Assessment of Jiles-Atherton Parameter Estimation for Inrush Current Studies
In this context, this research work presents a framework to assess the impact of different parameter initialization strategies on the performance of the JA parameter estimation for inrush current studies.
Residual-based Attention Physics-informed Neural Networks for Spatio-Temporal Ageing Assessment of Transformers Operated in Renewable Power Plants
Thermal insulation ageing is a key transformer failure mode, which is generally tracked by monitoring the hotspot temperature (HST).
A Hybrid Probabilistic Battery Health Management Approach for Robust Inspection Drone Operations
The performance of the hybrid probabilistic methodology was empirically evaluated on a dataset comprising EOD voltage under varying load conditions.
