This study investigates the theoretical formulations and practical applications of fractal algorithms, integrative computational frameworks, and recursive methodologies in modeling complex systems. Within the context of mathematical modeling, the fundamental principles of self-similarity and scale invariance are analyzed alongside their structural significance in non-linear dynamic systems. By deploying integrative approaches, the interdisciplinary interconnectivity and temporal dynamics of complex processes across various scientific domains are systematically examined, highlighting their practical implementation potential. Furthermore, the paper elucidates the foundational role of Chaos Theory in uncovering non-linear linkages and sensitive dependencies inherent to fractal architectures and chaotic attractors. The findings provide comprehensive perspectives on the synergistic integration of recursive algorithms and fractal geometry, establishing robust computational paradigms for modern complex systems analysis.
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J.Sh. Khursanboyev (2026) studied this question.
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