Neuro-fuzzy modeling of deformation parameters for fusion-barriers
The fusion-barrier distribution is very sensitive to the structure of the colliding nuclei such as nuclear quadrupole and hexadecapole deformation parameters and their signs. If the nuclei that enter the fusion reaction are deformed, the barrier problem becomes complicated. Therefore the deformation...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-05-01
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| Series: | Nuclear Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573320309104 |
| _version_ | 1819076445716086784 |
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| author | Serkan Akkoyun Yunis Torun |
| author_facet | Serkan Akkoyun Yunis Torun |
| author_sort | Serkan Akkoyun |
| collection | DOAJ |
| description | The fusion-barrier distribution is very sensitive to the structure of the colliding nuclei such as nuclear quadrupole and hexadecapole deformation parameters and their signs. If the nuclei that enter the fusion reaction are deformed, the barrier problem becomes complicated. Therefore the deformation parameters are taken into account in the calculations. In this study, Neuro-Fuzzy approach, ANFIS, method has been used for the estimation of ground-state quadrupole (ε2) and hexadecapole (ε4) deformation parameters for the nuclei. According to the results, the method is suitable for this task and one can confidently use it to obtain the data that is not available in the literature. |
| first_indexed | 2024-12-21T18:41:25Z |
| format | Article |
| id | doaj.art-db8da84d2e2742a890e12b9f0f86e2c0 |
| institution | Directory Open Access Journal |
| issn | 1738-5733 |
| language | English |
| last_indexed | 2024-12-21T18:41:25Z |
| publishDate | 2021-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Nuclear Engineering and Technology |
| spelling | doaj.art-db8da84d2e2742a890e12b9f0f86e2c02022-12-21T18:54:00ZengElsevierNuclear Engineering and Technology1738-57332021-05-0153516121618Neuro-fuzzy modeling of deformation parameters for fusion-barriersSerkan Akkoyun0Yunis Torun1Department of Physics, Faculty of Sciences, Sivas Cumhuriyet University, Sivas, Turkey; Artificial Intelligence Systems and Data Science Application and Research Center, Sivas Cumhuriyet University, Sivas, Turkey; Corresponding author. Department of Physics, Faculty of Sciences, Sivas Cumhuriyet University, Sivas, Turkey.Department of Electric-Electronics Engineering, Sivas Cumhuriyet University, Sivas, Turkey; Artificial Intelligence Systems and Data Science Application and Research Center, Sivas Cumhuriyet University, Sivas, TurkeyThe fusion-barrier distribution is very sensitive to the structure of the colliding nuclei such as nuclear quadrupole and hexadecapole deformation parameters and their signs. If the nuclei that enter the fusion reaction are deformed, the barrier problem becomes complicated. Therefore the deformation parameters are taken into account in the calculations. In this study, Neuro-Fuzzy approach, ANFIS, method has been used for the estimation of ground-state quadrupole (ε2) and hexadecapole (ε4) deformation parameters for the nuclei. According to the results, the method is suitable for this task and one can confidently use it to obtain the data that is not available in the literature.http://www.sciencedirect.com/science/article/pii/S1738573320309104Deformation deformationNilsson parametersArtificial intelligenceANFIS |
| spellingShingle | Serkan Akkoyun Yunis Torun Neuro-fuzzy modeling of deformation parameters for fusion-barriers Nuclear Engineering and Technology Deformation deformation Nilsson parameters Artificial intelligence ANFIS |
| title | Neuro-fuzzy modeling of deformation parameters for fusion-barriers |
| title_full | Neuro-fuzzy modeling of deformation parameters for fusion-barriers |
| title_fullStr | Neuro-fuzzy modeling of deformation parameters for fusion-barriers |
| title_full_unstemmed | Neuro-fuzzy modeling of deformation parameters for fusion-barriers |
| title_short | Neuro-fuzzy modeling of deformation parameters for fusion-barriers |
| title_sort | neuro fuzzy modeling of deformation parameters for fusion barriers |
| topic | Deformation deformation Nilsson parameters Artificial intelligence ANFIS |
| url | http://www.sciencedirect.com/science/article/pii/S1738573320309104 |
| work_keys_str_mv | AT serkanakkoyun neurofuzzymodelingofdeformationparametersforfusionbarriers AT yunistorun neurofuzzymodelingofdeformationparametersforfusionbarriers |