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Being a summary, our benefits on the numerical experiments demonstrate that parameter-based mostly transfer learning does assistance forecast disruptions in upcoming tokamak with constrained details, and outperforms other procedures to a big extent. On top of that, the layers inside the ParallelConv1D blocks are able to extracting standard and very

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