内蒙古民族大学学报（自然科学版）2025，Vol.40Issue(2)：16-22,7.DOI:10.14045/j.cnki.15-1220.2025.02.003
中低能质子与铜反应截面的贝叶斯神经网络计算研究
Bayesian Neural Network Calculation of the Cross-section of the Reaction Between Medium and Low Energy Protons and Copper
摘要
Abstract
The product cross-section data from proton-induced spallation reactions serves as a crucial founda-tion for many nuclear reaction applications.However,due to the complexity of the systems involved and the wide en-ergy range of spallation reactions and the reaction energy exceeding 3-4 orders of magnitude,current theoretical models still face limitations in accurately predicting cross-sections.In order to obtain higher prediction accuracy,Bayesian Neural Networks(BNN)method was used to model and analyze the spallation reaction cross-sections of protons with a copper(Cu)target.Compared with traditional methods,BNN can provide high-precision predictions by learning from experimental data and quantify the uncertainty in predictions.Based on experimental data from the EXFOR database,the constructed BNN model accurately predicted reaction cross-sections across multiple energy ranges,and is verified with experimental data.Results show that the BNN model demonstrates excellent predictive capability across a broad energy spectrum and,especially in regions with sparse data,effectively quantifies the un-certainty through reasonable confidence intervals.关键词
贝叶斯神经网络/余核截面/natCuKey words
Bayesian Neural Networks/residual core cross-section/natCu分类
数理科学引用本文复制引用
黄永顺,黄美容,张苏雅拉吐..中低能质子与铜反应截面的贝叶斯神经网络计算研究[J].内蒙古民族大学学报（自然科学版）,2025,40(2):16-22,7.基金项目
国家自然科学基金项目(12365018) （12365018）
内蒙古自治区高等学校青年科技英才支持计划项目(NJYT23109) （NJYT23109）
内蒙古自治区高等学校创新团队发展支持计划项目(NMGIRT2217) （NMGIRT2217）
内蒙古自治区直属高校基本科研业务费项目(GXKY22061) （GXKY22061）
内蒙古自治区自然科学基金项目(2023MS01005) （2023MS01005）
