Novel Evaluation of Fuzzy Fractional Biological Population Model

This article discusses an iterative transformation method via fuzziness that mixtures the Laplace transform with the iterative iterative method. Using Caputo derivative operator, the proposed technique demonstrates the inherent reliability of fractional fuzzy biological population equations with ini...

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Main Authors: Rabab Alyusof, Shams Alyusof, Naveed Iqbal, Sallieu Kabay Samura
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Function Spaces
Online Access:http://dx.doi.org/10.1155/2022/4355938
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author Rabab Alyusof
Shams Alyusof
Naveed Iqbal
Sallieu Kabay Samura
author_facet Rabab Alyusof
Shams Alyusof
Naveed Iqbal
Sallieu Kabay Samura
author_sort Rabab Alyusof
collection DOAJ
description This article discusses an iterative transformation method via fuzziness that mixtures the Laplace transform with the iterative iterative method. Using Caputo derivative operator, the proposed technique demonstrates the inherent reliability of fractional fuzzy biological population equations with initial fuzzy conditions. The obtained results to the fuzzy fractional biological equations are more general and apply to a broad variety of problems. A parametric description of the solutions is obtained by translating the fuzzy fractional differential equation into an equivalent system of corresponding fractional differential equations. The proposed method is numerically tested against crisp solutions and those produced by other methods, demonstrating that it is a convenient and remarkably accurate way to solve a tool for solving a wide variety of physics and engineering problems.
format Article
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institution OA Journals
issn 2314-8888
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Journal of Function Spaces
spelling doaj-art-b25779dea3f74e8d884dedfb05e173f12025-08-20T02:23:19ZengWileyJournal of Function Spaces2314-88882022-01-01202210.1155/2022/4355938Novel Evaluation of Fuzzy Fractional Biological Population ModelRabab Alyusof0Shams Alyusof1Naveed Iqbal2Sallieu Kabay Samura3Department of MathematicsDepartment of MathematicsDepartment of MathematicsDepartment of Mathematics and StatisticsThis article discusses an iterative transformation method via fuzziness that mixtures the Laplace transform with the iterative iterative method. Using Caputo derivative operator, the proposed technique demonstrates the inherent reliability of fractional fuzzy biological population equations with initial fuzzy conditions. The obtained results to the fuzzy fractional biological equations are more general and apply to a broad variety of problems. A parametric description of the solutions is obtained by translating the fuzzy fractional differential equation into an equivalent system of corresponding fractional differential equations. The proposed method is numerically tested against crisp solutions and those produced by other methods, demonstrating that it is a convenient and remarkably accurate way to solve a tool for solving a wide variety of physics and engineering problems.http://dx.doi.org/10.1155/2022/4355938
spellingShingle Rabab Alyusof
Shams Alyusof
Naveed Iqbal
Sallieu Kabay Samura
Novel Evaluation of Fuzzy Fractional Biological Population Model
Journal of Function Spaces
title Novel Evaluation of Fuzzy Fractional Biological Population Model
title_full Novel Evaluation of Fuzzy Fractional Biological Population Model
title_fullStr Novel Evaluation of Fuzzy Fractional Biological Population Model
title_full_unstemmed Novel Evaluation of Fuzzy Fractional Biological Population Model
title_short Novel Evaluation of Fuzzy Fractional Biological Population Model
title_sort novel evaluation of fuzzy fractional biological population model
url http://dx.doi.org/10.1155/2022/4355938
work_keys_str_mv AT rababalyusof novelevaluationoffuzzyfractionalbiologicalpopulationmodel
AT shamsalyusof novelevaluationoffuzzyfractionalbiologicalpopulationmodel
AT naveediqbal novelevaluationoffuzzyfractionalbiologicalpopulationmodel
AT sallieukabaysamura novelevaluationoffuzzyfractionalbiologicalpopulationmodel