Neutron-alpha reaction cross section determination by machine learning approaches
Yükleniyor...
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
This study focuses on leveraging powerful machine learning approaches to determine neutron- alpha reaction cross-sections within the 14–15 MeV energy range. The investigation utilizes an experimental dataset comprising measurements of 133 nuclei concerning (n, ?) reaction cross- sections. These data are divided into training and validation subsets, following established protocols, with 80% allocated for model training and 20% for testing. Key nucleus characteristics, including neutron number (N), mass number (A), and symmetry representation [(N-Z)²/A], were used as input variables for the machine learning models. SVR and XGBoost methods showed superior performance among the other machine learning methods used in the present study. In addition, a machine learning based online calculation tool was developed to estimate the reaction cross section.
Açıklama
Anahtar Kelimeler
(n, α) Reaction, Machine-Learning, Reaction Cross-Section
Kaynak
Journal of Fusion Energy
WoS Q Değeri
Q1
Scopus Q Değeri
Q2
Cilt
43
Sayı
2
