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A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics
This paper proposes a three-step iterative technique for solving nonlinear equations from medical science. We designed the proposed technique by blending the well-known Newton's method with an existing two-step technique. The method needs only five evaluations per iteration: three for the given...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352491/ https://www.ncbi.nlm.nih.gov/pubmed/35936367 http://dx.doi.org/10.1155/2022/7656451 |
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author | Qureshi, Sania Soomro, Amanullah Shaikh, Asif Ali Hincal, Evren Gokbulut, Nezihal |
author_facet | Qureshi, Sania Soomro, Amanullah Shaikh, Asif Ali Hincal, Evren Gokbulut, Nezihal |
author_sort | Qureshi, Sania |
collection | PubMed |
description | This paper proposes a three-step iterative technique for solving nonlinear equations from medical science. We designed the proposed technique by blending the well-known Newton's method with an existing two-step technique. The method needs only five evaluations per iteration: three for the given function and two for its first derivatives. As a result, the novel approach converges faster than many existing techniques. We investigated several models of applied medical science in both scalar and vector versions, including population growth, blood rheology, and neurophysiology. Finally, some complex-valued polynomials are shown as polynomiographs to visualize the convergence zones. |
format | Online Article Text |
id | pubmed-9352491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93524912022-08-05 A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics Qureshi, Sania Soomro, Amanullah Shaikh, Asif Ali Hincal, Evren Gokbulut, Nezihal Comput Math Methods Med Research Article This paper proposes a three-step iterative technique for solving nonlinear equations from medical science. We designed the proposed technique by blending the well-known Newton's method with an existing two-step technique. The method needs only five evaluations per iteration: three for the given function and two for its first derivatives. As a result, the novel approach converges faster than many existing techniques. We investigated several models of applied medical science in both scalar and vector versions, including population growth, blood rheology, and neurophysiology. Finally, some complex-valued polynomials are shown as polynomiographs to visualize the convergence zones. Hindawi 2022-07-28 /pmc/articles/PMC9352491/ /pubmed/35936367 http://dx.doi.org/10.1155/2022/7656451 Text en Copyright © 2022 Sania Qureshi et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Qureshi, Sania Soomro, Amanullah Shaikh, Asif Ali Hincal, Evren Gokbulut, Nezihal A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title | A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title_full | A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title_fullStr | A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title_full_unstemmed | A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title_short | A Novel Multistep Iterative Technique for Models in Medical Sciences with Complex Dynamics |
title_sort | novel multistep iterative technique for models in medical sciences with complex dynamics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352491/ https://www.ncbi.nlm.nih.gov/pubmed/35936367 http://dx.doi.org/10.1155/2022/7656451 |
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