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Line 34: == Data-driven reliability predictions == Data-driven models for reliability prediction utilise data acquired from tests to failure on electronic components by establishing relationships between the different variables presented in the data. As such relationships can be complex, data-driven models often require computations in high dimensions, which means that a large dataset is needed to optimize the output of the model.<ref>{{cite conference \|last1=Ghrabli \|first1=Mehdi\|last2=Bouarroudj \|first2=Mounira \| author3=Chamoin, Ludovic\|author4=Aldea, Emanuel \|date=2024 \|title=Hybrid modeling for remaining useful life prediction in power module prognosis \|url=https://ieeexplore.ieee.org/document/10491493 \|conference=2024 25th International Conference on Thermal Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)\|___location=Catania, Italy \|publisher=IEEE\|doi=10.1109/EuroSimE60745.2024.10491493 \|url-access=subscription }}</ref> == Physics-based reliability predictions ==

Reliability prediction for electronic components: Difference between revisions