In recent years, machine learning (ML) methods have emerged as crucial tools in inertial confinement fusion (ICF) research. This paper compiles ML algorithms employed in ICF studies over the past decade, elucidates their operational principles, distinctive features, and application scenarios, provides representative implementation cases, and analyzes developmental trends within this interdisciplinary domain.
Disclaimer: The English version of this article is automatically generated by Baidu Translation and only for reference. We therefore are not responsible for its reasonableness, correctness and completeness, and will not bear any commercial and legal responsibilities for the relevant consequences arising from the English translation.
DownLoad: