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Individuals that usually do not qualify in the ultimate evaluation, and those who were being absent can get anoter opportunity to move the tenth class by way of these tests.
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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。
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854 discharges (525 disruptive) out of 2017�?018 compaigns are picked out from J-Textual content. The discharges address all the channels we selected as inputs, and include all types of disruptions in J-TEXT. Most of the dropped disruptive discharges ended up induced manually and did not display any signal of instability ahead of disruption, like the ones with MGI (Huge Gas Injection). Moreover, some discharges had been dropped resulting from invalid details in the vast majority of enter channels. It is tough to the model while in the goal area to outperform that inside the source area in transfer Discovering. Consequently the pre-qualified model within the source area is expected to incorporate as much facts as you possibly can. In this case, the pre-qualified product with J-TEXT discharges is purported to obtain just as much disruptive-relevant information as you can. Consequently the discharges decided on from J-TEXT are randomly shuffled and break up into education, validation, and test sets. The teaching set consists of 494 discharges (189 disruptive), when the validation set incorporates a hundred and forty discharges (70 disruptive) as well as the exam set incorporates 220 discharges (a hundred and ten disruptive). Normally, to simulate authentic operational scenarios, the design must be trained with knowledge from earlier campaigns and analyzed with information from afterwards ones, Because the overall performance in the product may be degraded because the experimental environments fluctuate in various strategies. A model adequate in one marketing campaign is probably not as adequate for your new marketing campaign, which is the “ageing dilemma�? Having said that, when training the supply design on J-Textual content, we care more about disruption-connected expertise. As a result, we break up our facts sets randomly in J-Textual content.
The purpose of this investigation is always to Enhance the disruption prediction performance on concentrate on tokamak with mainly knowledge from your source tokamak. The design effectiveness on focus on area mostly depends on the efficiency on the design during the supply domain36. As a result, we initially have to have to acquire a superior-functionality pre-qualified model with J-Textual content information.
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买的炉石号是换不了绑定身份证和手机的，当时店主跟我说那些是si体信息不换也没事。只能改密码换绑定邮箱
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