eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices
Introduction: This work explores the use of eXplainable artificial intelligence (XAI) to analyze a convolutional neural network (CNN) trained for disruption prediction in tokamak devices and fed with inputs composed of different physical quantities.Methods: This work focuses on a reduced dataset con...
| الحاوية / القاعدة: | Frontiers in Physics |
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| المؤلفون الرئيسيون: | , , , , , , , , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Frontiers Media S.A.
2024-05-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.frontiersin.org/articles/10.3389/fphy.2024.1359656/full |
