Study of photoneutron reaction based on physics-informed Bayesian neural network
Special Topics on Applications of Machine Learning in Nuclear Physics and Nuclear Data|更新时间:2025-05-24
|
Study of photoneutron reaction based on physics-informed Bayesian neural network
封面论文增强出版
“In the field of predicting the cross-section of photonuclear reactions, experts have significantly improved the training efficiency and prediction accuracy of the model based on Bayesian neural network optimization algorithms, providing strong support for resolving data discrepancies between laboratories.”
SUN Qiankun, male, born in 1998, graduated from Zhengzhou University in 2022, doctoral student, focusing on photonuclear physics
WANG Hongwei, E-mail: wanghw@sari.ac.cn
基金信息:
National Key Research and Development Program(2022YFA1602404;2023YFA1606901);National Natural Science Foundation of China(12388102;U2441221;12275338);the Key Laboratory of Nuclear Data foundation(JCKY2022201C152)
SUN Qiankun,ZHANG Yue,HAO Zirui,et al.Study of photoneutron reaction based on physics-informed Bayesian neural network[J].NUCLEAR TECHNIQUES,2025,48(05):050001.