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This makes them not contribute to predicting disruptions on long run tokamak with a different time scale. Nonetheless, even further discoveries during the physical mechanisms in plasma physics could probably contribute to scaling a normalized time scale across tokamaks. We should be able to receive a greater technique to procedure alerts in a larger time scale, to ensure that even the LSTM layers of the neural community should be able to extract common information and facts in diagnostics across diverse tokamaks in a bigger time scale. Our results demonstrate that parameter-based mostly transfer Mastering is powerful and it has the potential to predict disruptions in potential fusion reactors with distinct configurations.

实际上，“¥”符号中水平线的数量在不同的字体是不同的，但其含义相同。下表提供了一些字体的情况，其中“＝”表示为双水平线，“－”表示为单水平线，“×”表示无此字符。

Disruptions in magnetically confined plasmas share the same Bodily regulations. Nevertheless disruptions in various tokamaks with distinctive configurations belong for their respective domains, it is feasible to extract area-invariant characteristics throughout all tokamaks. Physics-driven function engineering, deep domain generalization, and also other illustration-based mostly transfer Understanding methods can be utilized in more research.

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前言：在日常编辑文本的过程中，许多人把比号“∶”与冒号“：”混淆，那它们的区别是什么？比号怎么输入呢？

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Different tokamaks personal various diagnostic techniques. Even so, They may be alleged to share a similar or equivalent Visit Website diagnostics for essential functions. To establish a aspect extractor for diagnostics to aid transferring to upcoming tokamaks, not less than two tokamaks with very similar diagnostic devices are expected. Moreover, taking into consideration the big quantity of diagnostics to be used, the tokamaks must also be capable of present adequate information masking various styles of disruptions for superior instruction, such as disruptions induced by density boundaries, locked modes, along with other explanations.

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Therefore, it is the best apply to freeze all levels from the ParallelConv1D blocks and only wonderful-tune the LSTM layers and the classifier without the need of unfreezing the frozen levels (case 2-a, plus the metrics are demonstrated in the event two in Desk 2). The levels frozen are thought of in the position to extract standard options throughout tokamaks, whilst the rest are thought to be tokamak precise.