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The Fusion Function Extractor (FFE) based mostly product is retrained with a person or numerous alerts of the same type neglected every time. Normally, the drop from the overall performance in comparison Together with the design experienced with all alerts is meant to point the importance of the dropped alerts. Alerts are purchased from major to base in lowering buy of relevance. It appears that the radiation arrays (comfortable X-ray (SXR) and absolutely the Excessive UltraViolet (AXUV) radiation measurement) include one of the most appropriate information and facts with disruptions on J-Textual content, with a sampling rate of only one kHz. Though the core channel of the radiation array isn't dropped and is also sampled with 10 kHz, the spatial info cannot be compensated.
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In addition, the performances of scenario 1-c, two-c, and three-c, which unfreezes the frozen layers and further tune them, are much even worse. The outcome suggest that, constrained data with the target tokamak will not be representative plenty of and also the prevalent understanding might be extra probably flooded with unique patterns through the source info which is able to lead to a worse general performance.
Performances amongst the a few models are proven in Desk one. The disruption predictor depending on FFE outperforms other designs. The product based on the SVM with guide attribute extraction also beats the overall deep neural community (NN) design by a big margin.
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¥符号由拉丁字母“Y”和平行水平线组成。使用拉丁字母“Y”的原因是因为“圆”的中文和日語在英文中的拼写“yuan”和“yen”的起始字母都是“Y”。
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