Fractals in $$S_b$$ -metric spaces

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Complex & Intelligent Systems Pub Date : 2025-04-03 DOI:10.1007/s40747-025-01849-1
Fahim Ud Din, Sheeza Nawaz, Adil Jhangeer, Fairouz Tchier
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Abstract

This study aims to discover attractors for fractals by using generalized F-contractive iterated function system, which falls within a distinct category of mappings defined on \(S_b\)-metric spaces. In particular, we investigate how these systems, when subjected to specific F-contractive conditions, can lead to the identification of a unique attractor. We achieve a diverse range of outcomes for iterated function systems that adhere to a unique set of generalized F-contractive conditions. Our approach includes a detailed theoretical framework that establishes the existence and uniqueness of attractors in these settings. We provide illustrative examples to bolster the findings established in this work and use the functions given in the example to construct fractals and discuss the convergence of the obtained fractals via iterated function system to an attractor. These examples demonstrate the practical application of our theoretical results, showcasing the convergence behavior of fractals generated by our proposed systems. These outcomes extend beyond the scope of various existing results found in the current body of literature. By expanding the applicability of F-contractive conditions, our findings contribute to the broader understanding of fractal geometry and its applications, offering new insights and potential directions for future research in this area.

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S_b$$$度量空间中的分形
本文旨在利用广义f -压缩迭代函数系统发现分形的吸引子,该系统属于\(S_b\) -度量空间上定义的映射的不同类别。特别是,我们研究了这些系统,当受到特定的f收缩条件时,如何导致唯一吸引子的识别。我们获得了迭代函数系统的各种结果,这些结果遵循一组唯一的广义f收缩条件。我们的方法包括一个详细的理论框架,在这些设置中建立吸引子的存在性和唯一性。我们提供了说明性的例子来支持在这项工作中建立的发现,并使用示例中给出的函数来构造分形,并讨论了通过迭代函数系统得到的分形收敛到吸引子。这些例子展示了我们的理论结果的实际应用,展示了我们提出的系统产生的分形的收敛行为。这些结果超出了当前文献中发现的各种现有结果的范围。通过扩展f压缩条件的适用性,我们的发现有助于更广泛地理解分形几何及其应用,为该领域的未来研究提供了新的见解和潜在的方向。
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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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