Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays
Abstract
1. Introduction
- The computer virus model (3) considered in this paper incorporates two distinct time delays. In contrast to several existing models in the literature, the introduction of multiple delays better reflects the realistic situation in which different compartments of the system may involve different delay effects. Moreover, the presence of distinct delays enriches the dynamical behavior of the system, thereby allowing for more flexible and realistic applications. In particular, the interaction between these delays may give rise to more complex phenomena, such as stability switching and multiple bifurcation scenarios. This further enhances the applicability of the model in describing real-world virus propagation processes and provides a more comprehensive framework for understanding the influence of delay effects on system dynamics.
- The model (3) is formulated as a fractional-order system with incommensurate orders in the Caputo sense. As indicated previously, the utilization of incommensurate fractional derivatives enhances the modeling capability by capturing memory and hereditary effects with greater flexibility, allowing different state variables to exhibit distinct memory characteristics. Compared with commensurate fractional-order models, this formulation provides a more general and realistic framework for describing complex dynamical processes. However, it also introduces significant mathematical challenges, particularly in the bifurcation analysis, due to the increased complexity of the characteristic equations, the lack of a unified fractional order, and the intricate stability conditions. These features make the analytical treatment more involved, while simultaneously enriching the potential dynamical behaviors of the system.
- The model (3) under consideration describes the propagation of computer viruses. We establish two results concerning the impact of two distinct time delays on the system dynamics and demonstrate that these delays can induce Hopf bifurcation in DFSLB (3). The analysis is conducted via linearization and the study of the associated characteristic equations, which provide explicit conditions for stability switching. Several numerical simulations are also conducted to validate and support the theoretical findings. The results obtained in this paper provide further insight into the mechanisms governing bifurcation phenomena in delayed fractional-order (incommensurate or not) computer virus models, and may facilitate the development of effective control strategies for mitigating virus propagation in complex networked systems.
2. Equilibria of DFSLB (3) and the Basic Reproduction Number
3. Hopf Bifurcation Results and Their Proofs
4. Numerical Simulations
5. Concluding Remarks
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
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Zhong, A.; Wang, C. Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays. Entropy 2026, 28, 787. https://doi.org/10.3390/e28070787
Zhong A, Wang C. Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays. Entropy. 2026; 28(7):787. https://doi.org/10.3390/e28070787
Chicago/Turabian StyleZhong, Ailing, and Chengqiang Wang. 2026. "Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays" Entropy 28, no. 7: 787. https://doi.org/10.3390/e28070787
APA StyleZhong, A., & Wang, C. (2026). Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays. Entropy, 28(7), 787. https://doi.org/10.3390/e28070787

