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结束语:比号又叫比值号,也叫比率号,在数学中的作用相当于除号÷。在行文中,冒号的作用一般是提示下文。返回搜狐,查看更多
Mixing knowledge from both of those concentrate on and current machines is A technique of transfer Finding out, occasion-based transfer Understanding. But the information carried from the confined info with the concentrate on device might be flooded by info from the existing equipment. These will work are completed among the tokamaks with similar configurations and measurements. However, the hole in between upcoming tokamak reactors and any tokamaks current currently is quite large23,24. Dimensions of the device, Procedure regimes, configurations, element distributions, disruption leads to, attribute paths, along with other things will all final result in different plasma performances and different disruption processes. So, in this operate we picked the J-Textual content and also the EAST tokamak which have a large change in configuration, operation regime, time scale, function distributions, and disruptive leads to, to exhibit the proposed transfer Understanding method.
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Additionally, there is still more likely for making much better use of data coupled with other sorts of transfer Finding out methods. Generating whole use of data is The main element to disruption prediction, specifically for foreseeable future fusion reactors. Parameter-based transfer Studying can function with One more process to additional Increase the transfer efficiency. Other techniques such as instance-based transfer Discovering can guideline the creation of the confined focus on tokamak facts used in the parameter-primarily based transfer method, to Enhance the transfer efficiency.
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Performances amongst the three versions are demonstrated in Desk 1. The disruption predictor determined by FFE outperforms other products. The model based upon the SVM with manual function extraction also beats the final deep neural network (NN) model by a major margin.
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In our situation, the FFE qualified on J-Textual content is expected in order to extract small-level characteristics throughout distinct tokamaks, for instance those linked to MHD instabilities in addition to other capabilities which might be common throughout different tokamaks. The best layers (layers closer for the output) of your pre-educated design, normally the classifier, in addition to the prime of Open Website your attribute extractor, are utilized for extracting large-stage capabilities specific to the source duties. The very best layers of the model are often high-quality-tuned or changed to make them much more pertinent to the goal process.
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