用图论方法和Simulink连接代数中的二分性和反转

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2025-09-29 DOI:10.1155/cplx/6053078
Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, M. I. Elashiry, Samuel Asefa Fufa
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引用次数: 0

摘要

几十年来的研究一直集中在代数结构图上,它以一种创新的方式结合了代数和组合学。本研究的目的是表征与特定代数结构相关的二部图和逆图的特定方面,如弱逆性质拟群及其同位素、对易子子环、结合子子环和核,重点关注结构和拓扑特征。本研究旨在强调数学代数系统与图论能力之间的联系,为通过Simulink在计算机科学中的理论进步和应用铺平道路。该方法将基于拟群结构分量的代数技术与简单图的基本思想通过边缘标记相结合。此外,数学方法用于属性分析、图形可视化和构造。分析表明,具有弱逆性质环的逆图和二部图具有不同的结构模式,如支持特定性质的子结构、连通性和顶点系统的对称性。最后,我们的发现为未来检测更复杂的代数结构和动态图模型奠定了基础,并为理论研究和实际应用提供了各种机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Linking Bipartiteness and Inversion in Algebra via Graph-Theoretic Methods and Simulink

Linking Bipartiteness and Inversion in Algebra via Graph-Theoretic Methods and Simulink

Research for decades has concentrated on graphs of algebraic structures, which integrate algebra and combinatorics in an innovative way. The goal of this study is to characterize specific aspects of bipartite and inverse graphs that are associated with specific algebraic structures, such as weak inverse property quasigroups and their isotopes, commutator subloops, associator subloops, and nuclei, with a focus on structural and topological characteristics. This research aims to highlight the link between mathematical algebraic systems and graph-theoretic capabilities, paving the path for theoretical advances and applications in computer science through Simulink. The methodology blends algebraic techniques based on quasigroup structural components with basic ideas of simple graphs via edge labeling. Furthermore, mathematical methods are used for property analysis, graph visualization, and construction. The analysis shows that inverse and bipartite graphs with weak inverse property loops have distinct structural patterns, such as supporting substructures of specific properties, connectedness, and symmetry in the vertex system. Finally, our findings lay the groundwork for future detection of more complex algebraic structures and dynamic graph models, as well as various opportunities for both theoretical research and practical application.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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