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Machine learning based energy confinement time extrapolation via multi-tokamak database
Predicting energy confinement time in future fusion devices like ITER is a significant challenge for traditional methods. This study introduces an advanced machine learning framework to address this. Our approach utilizes deep ensembles for robust uncertain…
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Predicting energy confinement time in future fusion devices like ITER is a significant challenge for traditional methods. This study introduces an advanced machine learning framework to address this. Our approach utilizes deep ensembles for robust uncertain…
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Predicting energy confinement time in future fusion devices like ITER is a significant challenge for traditional methods. This study introduces an advanced machine learning framework to address this. Our approach utilizes deep ensembles for robust uncertain…
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本地资源档案fusion-literature-242-1533.json本地档案 · catalog-2026-08-10