典型文献
Improvement of the Bayesian neural network to study the photoneutron yield cross sections
文献摘要：
This work is an attempt to improve the Bayesian neural network(BNN)for studying photoneutron yield cross sections as a function of the charge number Z,mass number A,and incident energy ε.The BNN was improved in terms of three aspects:numerical parameters,input layer,and network structure.First,by minimizing the deviations between the predictions and data,the numerical parameters,including the hidden layer number,hidden node number,and activation function,were selected.It was found that the BNN with three hidden layers,10 hidden nodes,and sigmoid activation function provided the smallest deviations.Second,based on known knowledge,such as the isospin dependence and shape effect,the optimal ground-state properties were selected as input neurons.Third,the Lorentzian function was applied to map the hidden nodes to the output cross sections,and the empirical formula of the Lorentzian parameters was applied to link some of the input nodes to the output cross sections.It was found that the last two aspects improved the predictions and avoided overfitting,especially for the axially deformed nucleus.
文献关键词：
中图分类号：
作者姓名：
Yong-Yi Li;Fan Zhang;Jun Su
作者机构：
Department of Computing,Changzhi University,Changzhi 046011,China;Department of Physics,Changzhi University,Changzhi 046011,China;Sino-French Institute of Nuclear Engineering and Technology,Sun Yat-sen University,Zhuhai 519082,China
文献出处：
引用格式：
[1]Yong-Yi Li;Fan Zhang;Jun Su-.Improvement of the Bayesian neural network to study the photoneutron yield cross sections)[J].核技术（英文版）,2022(11):1-9
A类：
photoneutron,BNN,isospin
B类：
Improvement,Bayesian,neural,network,yield,cross,sections,This,attempt,studying,function,charge,number,mass,incident,energy,was,improved,terms,three,aspects,numerical,parameters,input,structure,First,by,minimizing,deviations,between,predictions,data,including,hidden,activation,were,selected,It,found,that,layers,nodes,sigmoid,provided,smallest,Second,known,knowledge,such,dependence,shape,effect,optimal,ground,state,properties,neurons,Third,Lorentzian,applied,map,output,empirical,formula,link,some,last,avoided,overfitting,especially,axially,deformed,nucleus
AB值：
0.451833
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