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Series-form solutions of generalized fractional-fisher models with uncertainties using hybrid approach in Caputo sense

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  • Qayyum, Mubashir
  • Tahir, Aneeza
  • Saeed, Syed Tauseef
  • Akgül, Ali

Abstract

The field of fuzzy calculus has emerged as a powerful mathematical tool which can effectively deal with uncertainties and impressions that are common in real-world situations. In particular, it has proven useful in modeling and analysis of complex biological systems with uncertain parameters. The current study focuses on analysis of (n+1)-dimensional fractional Fisher equations (FFEs) in fuzzy environment. The objective is to provide semi-analytical solutions for fuzzy (n+1)- dimensional FFEs by considering Caputo-gH fractional derivative. The uncertainty in initial conditions is injected through triangular fuzzy numbers and obtained fuzzy (n+1)-dimensional FFEs are solved using hybrid of homotopy perturbation with Laplace transform in fuzzy-Caputo sense, which provides a powerful mathematical framework for examining complex behavior. The derived series solutions are validated against existing results from the literature and found to be improved. The obtained results are analyzed by means of determining the fuzzy solutions and residual errors at varying fractional orders, membership function, spatial coordinate x, and time t. These analytical findings are visualized in graphical form for ease of comprehension. The conducted study yields significant insights about the behavior of fractional model having uncertain conditions, and highlights the efficiency of proposed methodology. The results of this study have important implications for understanding the dynamics of biological systems with uncertainty, and hence can be useful in wide variety of applications in different fields such as ecology, epidemiology, and economics.

Suggested Citation

  • Qayyum, Mubashir & Tahir, Aneeza & Saeed, Syed Tauseef & Akgül, Ali, 2023. "Series-form solutions of generalized fractional-fisher models with uncertainties using hybrid approach in Caputo sense," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004034
    DOI: 10.1016/j.chaos.2023.113502
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    References listed on IDEAS

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    1. Fuzhang Wang & Muhammad Nawaz Khan & Imtiaz Ahmad & Hijaz Ahmad & Hanaa Abu-Zinadah & Yu-Ming Chu, 2022. "Numerical Solution Of Traveling Waves In Chemical Kinetics: Time-Fractional Fishers Equations," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(02), pages 1-11, March.
    2. Mubashir Qayyum & Sidra Afzal & Efaza Ahmad & Serkan Araci, 2023. "Fractional Modeling of Non-Newtonian Casson Fluid between Two Parallel Plates," Journal of Mathematics, Hindawi, vol. 2023, pages 1-12, March.
    3. Sartanpara, Parthkumar P. & Meher, Ramakanta, 2023. "Solution of generalised fuzzy fractional Kaup–Kupershmidt equation using a robust multi parametric approach and a novel transform," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 939-969.
    4. Hosseininia, M. & Heydari, M.H. & Avazzadeh, Z., 2022. "Orthonormal shifted discrete Legendre polynomials for the variable-order fractional extended Fisher–Kolmogorov equation," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    5. Fan Zhang & Heng-You Lan & Hai-Yang Xu, 2022. "Generalized Hukuhara Weak Solutions for a Class of Coupled Systems of Fuzzy Fractional Order Partial Differential Equations without Lipschitz Conditions," Mathematics, MDPI, vol. 10(21), pages 1-21, October.
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    Cited by:

    1. Ma, Zhiying & Hou, Jie & Zhu, Wenhao & Peng, Yaxin & Li, Ying, 2023. "PMNN: Physical model-driven neural network for solving time-fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).

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