Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

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In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

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We develop a model-free approach to optimally control stochastic, Markovian systems subject to a reach-avoid constraint. Specifically, the state trajectory must remain within a safe set while reaching a target set within a finite time horizon. Due to the t ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Chattez avec Graph Search

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