A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model

Aslı Alkan; Halil Anaç

doi:10.17798/bitlisfen.1822685

A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model

Abstract

This paper presents a novel Caputo–Fabrizio hybrid numerical method for examining the dynamics of fractional epidemic models defined by memory effects and non-singular kernels. The proposed method combines the Caputo–Fabrizio fractional derivative with a hybrid transform framework, facilitating the derivation of accurate and convergent approximate solutions for nonlinear epidemic systems. The model's parameters are analyzed in relation to infection transmission and recovery dynamics, whereas the fractional order α regulates the magnitude of memory and genetic influences. Numerical simulations indicate that the novel hybrid method exhibits remarkable concordance with established results for integer-order scenarios, while showcasing enhanced precision, computing efficiency, and robustness in fractional contexts. The suggested method offers a versatile and effective analytical instrument for investigating real-world epidemic occurrences exhibiting long-term memory traits.

Keywords

Ethical Statement

The study is complied with research and publication ethics

Thanks

We would like to thank the referees and editors for their valuable contributions.

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Details

Primary Language

English

Subjects

Numerical Solution of Differential and Integral Equations

Journal Section

Research Article

Authors

Aslı Alkan
0000-0002-1036-7178
Türkiye

Halil Anaç ^*
0000-0002-1316-3947
Türkiye

Publication Date

June 30, 2026

Submission Date

November 12, 2025

Acceptance Date

May 5, 2026

Published in Issue

Year 2026 Volume: 15 Number: 2

DOI

https://doi.org/10.17798/bitlisfen.1822685

IZ

https://izlik.org/JA25PW73CF

Cite

RIS / Bibtex

APA

Alkan, A., & Anaç, H. (2026). A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 15(2), 726-740. https://doi.org/10.17798/bitlisfen.1822685

AMA

1.Alkan A, Anaç H. A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2026;15(2):726-740. doi:10.17798/bitlisfen.1822685

Chicago

Alkan, Aslı, and Halil Anaç. 2026. “A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 15 (2): 726-40. https://doi.org/10.17798/bitlisfen.1822685.

EndNote

Alkan A, Anaç H (June 1, 2026) A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 15 2 726–740.

IEEE

[1]A. Alkan and H. Anaç, “A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, vol. 15, no. 2, pp. 726–740, June 2026, doi: 10.17798/bitlisfen.1822685.

ISNAD

Alkan, Aslı - Anaç, Halil. “A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 15/2 (June 1, 2026): 726-740. https://doi.org/10.17798/bitlisfen.1822685.

JAMA

1.Alkan A, Anaç H. A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2026;15:726–740.

MLA

Alkan, Aslı, and Halil Anaç. “A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model”. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, vol. 15, no. 2, June 2026, pp. 726-40, doi:10.17798/bitlisfen.1822685.

Vancouver

1.Aslı Alkan, Halil Anaç. A New Caputo-Fabrizio Hybrid Method for the Numerical Solution of Caputo-Fabrizio Fractional Epidemic Model. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 2026 Jun. 1;15(2):726-40. doi:10.17798/bitlisfen.1822685