Analyzing population dynamics models via Sumudu transform
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arXiv
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| Format: | Preprint |
| Published: |
2021
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| _version_ | 1866909734454427648 |
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| author | Aibinu, M. O. Moyo, S. C. Moyo, S. |
| author_facet | Aibinu, M. O. Moyo, S. C. Moyo, S. |
| contents | This study demonstrates how to construct the solutions of a more general form of population dynamics models via a blend of variational iterative method with Sumudu transform. In this paper, population growth models are formulated in the form of delay differential equations of pantograph type which is a general form for the existing models. Innovative ways are presented for obtaining the solutions of population growth models where other analytic methods fail. Stimulating procedures for finding patterns and regularities in seemingly chaotic processes have been elucidated in this paper. How, when and why the changes in population sizes occur can be deduced through this study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2112_07126 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Analyzing population dynamics models via Sumudu transform Aibinu, M. O. Moyo, S. C. Moyo, S. Populations and Evolution Functional Analysis 34A08, 65M70, 33C45 This study demonstrates how to construct the solutions of a more general form of population dynamics models via a blend of variational iterative method with Sumudu transform. In this paper, population growth models are formulated in the form of delay differential equations of pantograph type which is a general form for the existing models. Innovative ways are presented for obtaining the solutions of population growth models where other analytic methods fail. Stimulating procedures for finding patterns and regularities in seemingly chaotic processes have been elucidated in this paper. How, when and why the changes in population sizes occur can be deduced through this study. |
| title | Analyzing population dynamics models via Sumudu transform |
| topic | Populations and Evolution Functional Analysis 34A08, 65M70, 33C45 |
| url | https://arxiv.org/abs/2112.07126 |