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Journals / Chaos Theory and Applications / 2026 / Volume: 5 Issue: 1

Analysis of Nonlinear Mathematical Model of COVID-19 via Fractional-Order Piecewise Derivative

Muhammad Sinan(University of Electronic Science and Technology of China)0000-0003-2177-3806
Kamal Shah(Prince Sultan University)0000-0002-8851-4844
Thabet Abdeljawad(University of Malakand)0000-0002-8889-3768
Ali Akgul(SIIRT UNIVERSITY)0000-0001-9832-1424
Pages
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Publication Date
2023-03-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

All the results are presented graphically.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Short memory and long memory terms are excellently explained using the concept of piecewise fractional order derivatives.
📊
Key Findings & Data:In this research work, we investigate dynamical systems addressing COVID-19 under piecewise equations with fractional order derivative (FOD).
💡
Conclusion & Impact:All the results are presented graphically.
🔬Design:Modeling & Simulation
📍Scope:2016 Verileri
⚙️Variables:Nonlinear dynamical system · Crossover behavior · Mathematical biology

Abstract

Short memory and long memory terms are excellently explained using the concept of piecewise fractional order derivatives. In this research work, we investigate dynamical systems addressing COVID-19 under piecewise equations with fractional order derivative (FOD). Here, we study the sensitivity of the proposed model by using some tools from the nonlinear analysis. Additionally, we develop a numerical scheme to simulate the model against various fractional orders by using Matlab 2016. All the results are presented graphically.

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Cite This Article

Sinan, M., Shah, K., Abdeljawad, T., Akgul, A. (2023). Analysis of Nonlinear Mathematical Model of COVID-19 via Fractional-Order Piecewise Derivative. Chaos Theory and Applications, Volume: 5 Issue: 1. https://doi.org/10.51537/chaos.1210461

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