现代应用物理2025，Vol.16Issue(1)：26-32,104,8.DOI:10.12061/j.issn.2095-6223.202410004
机器学习在辐射效应领域的应用现状与展望
Current Status and Prospect of Machine Learning Applied in the Field of Radiation Effects
摘要
Abstract
The machine learning has been applied to various branches of the research field of radiation effects.It can evaluate radiation hardened performance,failure characterization,and failure rule of universal electronics in radiation environment by experiment or simulation.Furthermore,a series of work are carried out with machine learning based on the conventional experimental observation,theoretical deduction and simulation,such as radiation effects monitoring,radiation effects sensitivity prediction,environment detection of radiation intensity,and radiation hardened by design.In this paper,the application of machine learning in the field of radiation effects is reviewed.The background,methods,and typical results of machine learning applied to the following five aspects are introduced,including radiation effects research of electronics which load machine learning algorithms,radiation effects monitoring,prediction of radiation effects sensitivity,environment detection of radiation intensities,and radiation hardened by design.Finally,discussions are presented about the future work.关键词
机器学习/电子器件/辐射效应/应用/现状与展望Key words
machine learning/electronic devices/radiation effects/application/status and prospect分类
能源科技引用本文复制引用
丁李利,薛院院,王晨辉,王百川,王坦,陈伟..机器学习在辐射效应领域的应用现状与展望[J].现代应用物理,2025,16(1):26-32,104,8.基金项目
国家自然科学基金资助项目(12375275) （12375275）
