Research Article
Fractional-Order Delayed Epidemic Models in Memory-Based Probabilistic Controlled Metric Spaces via Fixed Point Theory
* Corresponding author
Abstract
We introduce memory-based probabilistic controlled metric spaces and establish a non-Markovian contraction principle that extends the Banach fixed point theorem by depending on a finite number of previous iterates. This framework is suited for systems with delay, hereditary effects, and fractional dynamics. We prove unique existence and convergence of Picard iterations under memory-based probabilistic contractions. As an application, we analyze a fractional-order delayed epidemic model with memory and incubation effects, showing convergence to a unique equilibrium. These results provide a unified tool for fractional epidemic dynamics with delay and memory.
How to Cite
M. A. Khan, A. Shoaib, T. Abdeljawad, A. Mukheimer, Fractional-Order Delayed Epidemic Models in Memory-Based Probabilistic Controlled Metric Spaces via Fixed Point Theory, Int. J. Anal. Appl. 24 (2026), 195. https://doi.org/10.28924/2291-8639-24-2026-195
BibTeX
@article{Khan2026,
author = {Khan, Mahmood Akhtar and Shoaib, Abdullah and Abdeljawad, Thabet and Mukheimer, Aiman},
title = {Fractional-Order Delayed Epidemic Models in Memory-Based Probabilistic Controlled Metric Spaces via Fixed Point Theory},
journal = {Int. J. Anal. Appl.},
volume = {24},
year = {2026},
pages = {195},
doi = {10.28924/2291-8639-24-2026-195}
}References
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