Research article

Fractal attractors of iterated function systems in extended fuzzy $ \mathscr{F} $-metric spaces

  • Published: 29 September 2026
  • MSC : 03E72, 28A80, 47H09, 47H10, 54A40, 54E50

  • Certain fractal and fuzzy dynamical systems involve auxiliary control functions that exhibit irregular features such as non-monotonicity or discontinuities, placing them outside the scope of classical fuzzy metric frameworks. To analyze these dynamics, we introduce the concept of an extended fuzzy $ \mathscr{F} $-metric space and establish basic and fixed-point results in this setting. As an application of the fixed-point results, we use the framework to analyze Hutchinson–Barnsley operators arising in iterated function systems, providing a convergence analysis, a numerical simulation, and visualizations of fractal attractors on the Cantor set. This perspective aligns fixed-point techniques more closely with the analytical demands of fractal and fuzzy dynamic modeling. The proposed framework may also be a flexible mathematical setting for studying nonlinear systems involving uncertainty, including potential applications in environmental modeling, energy systems, and resource management.

    Citation: Abhishikta Das, Dipti Barman, Mohammad Sajid, Tarapada Bag. Fractal attractors of iterated function systems in extended fuzzy $ \mathscr{F} $-metric spaces[J]. AIMS Mathematics, 2026, 11(9): 32109-32156. doi: 10.3934/math.20261262

    Related Papers:

  • Certain fractal and fuzzy dynamical systems involve auxiliary control functions that exhibit irregular features such as non-monotonicity or discontinuities, placing them outside the scope of classical fuzzy metric frameworks. To analyze these dynamics, we introduce the concept of an extended fuzzy $ \mathscr{F} $-metric space and establish basic and fixed-point results in this setting. As an application of the fixed-point results, we use the framework to analyze Hutchinson–Barnsley operators arising in iterated function systems, providing a convergence analysis, a numerical simulation, and visualizations of fractal attractors on the Cantor set. This perspective aligns fixed-point techniques more closely with the analytical demands of fractal and fuzzy dynamic modeling. The proposed framework may also be a flexible mathematical setting for studying nonlinear systems involving uncertainty, including potential applications in environmental modeling, energy systems, and resource management.



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