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Characteristic engineering might reap the benefits of a fair broader domain awareness, which is not unique to disruption prediction duties and isn't going to require familiarity with disruptions. Then again, details-driven procedures learn from your wide amount of knowledge amassed over the years and possess attained excellent effectiveness, but deficiency interpretability12,13,14,fifteen,16,17,eighteen,19,twenty. Both equally methods benefit from the opposite: rule-centered approaches speed up the calculation by surrogate designs, although information-driven strategies benefit from area awareness When selecting enter indicators and developing the design. At present, both equally ways will need ample data with the target tokamak for instruction the predictors in advance of They are really applied. The vast majority of other solutions printed inside the literature target predicting disruptions especially for 1 gadget and lack generalization capacity. Considering that unmitigated disruptions of the high-functionality discharge would severely injury long term fusion reactor, it's complicated to build up more than enough disruptive data, Particularly at large functionality routine, to coach a usable disruption predictor.
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人工智能将带来怎样的学习未来—基于国际教育核心期刊和发展报告的质性元分析研究
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