Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model
This paper is analyzing Uranium clusters mathematically as well through artificial intelligence discrete fractional order model of four different phases. The model is classifying the decay into the Ni for i=1,2,3,4 with different convergence rates λi for i=1,2,3,4 and α⊛ and β. The model is first an...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Partial Differential Equations in Applied Mathematics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S266681812400442X |
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| author | Hasib Khan Jehad Alzabut D.K. Almutairi |
| author_facet | Hasib Khan Jehad Alzabut D.K. Almutairi |
| author_sort | Hasib Khan |
| collection | DOAJ |
| description | This paper is analyzing Uranium clusters mathematically as well through artificial intelligence discrete fractional order model of four different phases. The model is classifying the decay into the Ni for i=1,2,3,4 with different convergence rates λi for i=1,2,3,4 and α⊛ and β. The model is first analyzed for the mathematical validation including existence criteria and stability results. After these, a mathematical scheme based on the discretization is constructed and is applied to an initial data. The model is solved for the novel solutions and simulations for the fractional order 0.98 with variant parametric values. These results numerical results are then tested and affirmed with best validation performance by the use of artificial intelligence. We have observed a tremendous results of R=1 with normal distribution of the clustering data around the zero error. |
| format | Article |
| id | doaj-art-1fb8e0bd187a4bcd9d8ceec4c2fcb2ef |
| institution | Kabale University |
| issn | 2666-8181 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Partial Differential Equations in Applied Mathematics |
| spelling | doaj-art-1fb8e0bd187a4bcd9d8ceec4c2fcb2ef2025-01-08T04:53:45ZengElsevierPartial Differential Equations in Applied Mathematics2666-81812025-03-0113101056Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete modelHasib Khan0Jehad Alzabut1D.K. Almutairi2Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 66833, 11586 Riyadh, Saudi Arabia; Department of Mathematics, Shaheed Benazir Bhutto Uniersity, Sheringal, Dir Upper, Khyber Pakhtunkhwa, Pakistan; Corresponding author at: Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 66833, 11586 Riyadh, Saudi Arabia.Department of Mathematics and Sciences, Prince Sultan University, P.O. Box 66833, 11586 Riyadh, Saudi Arabia; Department of Industrial Engineering, OSTIM Technical University, 06374 Ankara, Turkiye; Center for Research and Innovation, Asia International University, Yangiobod MFY, G’ijduvon street, House 74, Bukhara, UzbekistanDepartment of Mathematics, College of Science Al-Zulfi, Majmaah University, 11952 Al-Majmaah, Saudi ArabiaThis paper is analyzing Uranium clusters mathematically as well through artificial intelligence discrete fractional order model of four different phases. The model is classifying the decay into the Ni for i=1,2,3,4 with different convergence rates λi for i=1,2,3,4 and α⊛ and β. The model is first analyzed for the mathematical validation including existence criteria and stability results. After these, a mathematical scheme based on the discretization is constructed and is applied to an initial data. The model is solved for the novel solutions and simulations for the fractional order 0.98 with variant parametric values. These results numerical results are then tested and affirmed with best validation performance by the use of artificial intelligence. We have observed a tremendous results of R=1 with normal distribution of the clustering data around the zero error.http://www.sciencedirect.com/science/article/pii/S266681812400442XCaputo’s difference operatorUranium decay analysisNumerical analysisMathematical analysisApplication of the artificial intelligence |
| spellingShingle | Hasib Khan Jehad Alzabut D.K. Almutairi Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model Partial Differential Equations in Applied Mathematics Caputo’s difference operator Uranium decay analysis Numerical analysis Mathematical analysis Application of the artificial intelligence |
| title | Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model |
| title_full | Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model |
| title_fullStr | Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model |
| title_full_unstemmed | Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model |
| title_short | Applications of artificial intelligence for clusters analysis of Uranium decay via a fractional order discrete model |
| title_sort | applications of artificial intelligence for clusters analysis of uranium decay via a fractional order discrete model |
| topic | Caputo’s difference operator Uranium decay analysis Numerical analysis Mathematical analysis Application of the artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S266681812400442X |
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