Fuzzy Fractional Cancer Tumor Model and Its Numerical Solution
Author Information
Author(s): Zureigat Hamzeh, Alshammari Saleh, Alshammari Mohammad, Al-Smadi Mohammed, Al-Sawallah M. Mossa
Primary Institution: Faculty of Science and Technology, Department of Mathematics, Jadara University, Irbid, Jordan
Hypothesis
How can fuzzy quantities improve the modeling of cancer tumor dynamics using fractional derivatives?
Conclusion
The study demonstrates that the fuzzy time-fractional cancer tumor model provides a more comprehensive understanding of tumor behavior, especially under uncertainty.
Supporting Evidence
- The fuzzy time-fractional cancer tumor model can handle uncertainties in initial conditions.
- The implicit method proposed is unconditionally stable, allowing for a broader range of scenarios.
- Numerical experiments showed strong agreement with exact solutions, validating the proposed approach.
Takeaway
This study looks at how fuzzy math can help us understand cancer better by using special equations that deal with uncertainty.
Methodology
An implicit finite difference method was developed to solve the fuzzy time-fractional cancer tumor model, and stability was assessed using the von Neumann method.
Limitations
The study does not address cases where the fractional order is less than 0.5.
Digital Object Identifier (DOI)
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