1 citations · 1 across the 3 of their papers we have counts for
3 papers
nucl-th2026
Further exploration of the machine-learning-based nuclear mass table
Liu Yaqi, Li Zhilong, Wang Yongjia +1
The mass of the atomic nucleus, as one of the fundamental physical quantities of the atomic nucleus, plays an important role in understanding and researching the structure of the a…
nucl-th2026
Machine learning the impact parameter in heavy-ion collisions at = 4 and 11 GeV: a cross-check study with UrQMD, AMPT, and JAM
Xiaoqing Yue, Guojun Wei, Yongjia Wang +7
By generating heavy-ion collision data with the ultrarelativistic quantum molecular dynamics (UrQMD) model, a multiphase transport (AMPT) model, and the JAM model, the impact param…
nucl-th2023★ 1 cited
Importance of physical information on the prediction of heavy-ion fusion cross section with machine learning
Zhilong Li, Zepeng Gao, Ling Liu +3
In this work, the Light Gradient Boosting Machine (LightGBM), which is a modern decision tree based machine-learning algorithm, is used to study the fusion cross section (CS) of he…