Abstract: In dynamic environments, optimization algorithms tend to track the changing optima. However, frequent changes to decision solutions often cause high switching costs and system instability.
Abstract: This letter proposes a sparse identification of nonlinear dynamics—physics informed neural network—particle swarm optimization algorithm for optimizing the air-gap design of transformers ...
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