An interpretable disruption predictor on EAST using improved XGBoost and SHAP
The development of a disruption predictor using a data-driven solution is an effective way to avoid or mitigate tokamak device disruptions. The black-box nature of the model itself determines the agnostic nature of its decision base and becomes a key factor limiting the further development of disrup...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Nuclear Fusion |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1741-4326/adeea8 |
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