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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Theoretically, the inputs must be mapped to (0, one) whenever they observe a Gaussian distribution. However, it's important to notice that not all inputs essentially follow a Gaussian distribution and for that reason may not be appropriate for this normalization strategy. Some inputs could have Extraordinary values that might have an affect on the normalization method. Consequently, we clipped any mapped values past (−5, 5) in order to avoid outliers with very massive values. Due to this fact, the ultimate selection of all normalized inputs Utilized in our Evaluation was between −five and five. A price of five was deemed appropriate for our design teaching as It is far from too significant to trigger concerns and can be massive plenty of to proficiently differentiate concerning outliers and ordinary values.
Various tokamaks have distinct diagnostic units. Nonetheless, They may be supposed to share the same or comparable diagnostics for necessary operations. To build a attribute extractor for diagnostics to support transferring to potential tokamaks, at the very least two tokamaks with similar diagnostic units are essential. Moreover, considering the massive quantity of diagnostics to be used, the tokamaks also needs to manage to give plenty of information covering several forms of disruptions for better teaching, for example disruptions induced by density boundaries, locked modes, along with other causes.
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比特币网络消耗大量的能量。这是因为在区块链上运行验证和记录交易的计算机需要大量的电力。随着越来越多的人使用比特币，越来越多的矿工加入比特币网络，维持比特币网络所需的能量将继续增长。
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A warning time of 5 ms is adequate for the Disruption Mitigation Process (DMS) to get impact on the J-TEXT tokamak. To ensure the DMS will consider influence (Massive Gasoline Injection (MGI) and foreseeable future mitigation solutions which might acquire a longer time), Visit Website a warning time bigger than ten ms are considered productive.
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Nuclear fusion energy could be the final word Electrical power for humankind. Tokamak could be the top applicant for any realistic nuclear fusion reactor. It uses magnetic fields to confine incredibly high temperature (100 million K) plasma. Disruption is a catastrophic loss of plasma confinement, which releases a great deal of energy and may cause serious damage to tokamak machine1,2,3,4. Disruption is without doubt one of the biggest hurdles in recognizing magnetically controlled fusion. DMS(Disruption Mitigation Procedure) such as MGI (Large Fuel Injection) and SPI (Shattered Pellet Injection) can correctly mitigate and alleviate the damage brought on by disruptions in present devices5,6. For giant tokamaks including ITER, unmitigated disruptions at large-functionality discharge are unacceptable. Predicting likely disruptions is really a crucial Think about proficiently triggering the DMS. Hence it is vital to precisely predict disruptions with enough warning time7. At the moment, There are 2 principal methods to disruption prediction exploration: rule-dependent and knowledge-driven procedures. Rule-based mostly techniques are based on The existing knowledge of disruption and focus on figuring out event chains and disruption paths and provide interpretability8,nine,10,eleven.