| Autor: |
Siagian, Ruben Cornelius, Alfaris, Lulut, Muhammad, Aldi Cahya, Nyuswantoro, Ukta Indra, Rancak, Gendewa Tunas |
| Předmět: |
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| Zdroj: |
Computer Engineering & Applications Journal; Oct2023, Vol. 12 Issue 3, p159-179, 21p |
| Abstrakt: |
This research article describes several analyses of nuclear data using various statistical methods. The first analysis uses linear regression to investigate the relationship between the independent variables (n and z) and the response variable (BE4DBE2). The second analysis uses a nonparametric regression model to overcome the assumptions of normality and linearity in the data. The third analysis uses the Naive Bayes method to classify nuclear data based on variables n and z. The fourth analysis uses a decision tree to classify nuclear data based on the same variables. Finally, the article describes an SVM analysis and a K-means analysis to classify and group nuclide data. The article presents clear and organized descriptions of each analysis, including visual representations of the results. The findings of each analysis are discussed, providing valuable insights into the relationships between the variables and the response variable. The article demonstrates the usefulness of statistical methods in analyzing nuclear data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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