一种在复杂网络中寻找社区结构的自然启发算法

Q3 Engineering

Journal of Applied Research and Technology Pub Date : 2023-06-27 DOI:10.22201/icat.24486736e.2023.21.3.1787

Bilal Saoud

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引用次数: 0

摘要

复杂的网络通常在社区中。这些社区非常重要。网络的社区代表了节点的集合，这些节点是紧密相连的。在这项研究中，我们开发了一种新的方法来寻找网络中的社区结构。我们的方法是基于花授粉算法(FPA)，它被用于分割过程。在我们的方法中，网络的分割最大化了一个称为模块化的质量函数。我们提供了一个通用的框架来实现我们在网络中寻找社区结构的新方法。通过与一些已知方法在计算机生成和现实世界网络上的比较，我们证明了我们的方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A nature-inspired algorithm to find community structure in complex networks

Complex networks have in generally communities. These communities are very important. Network’s communities represent sets of nodes, which are very connected. In this research, we developed a new method to find the community structure in networks. Our method is based on flower pollination algorithm (FPA) witch is used in the splitting process. The splitting of networks in our method maximizes a function of quality called modularity. We provide a general framework for implementing our new method to find community structure in networks. We present the effectiveness of our method by comparison with some known methods on computer-generated and real-world networks.

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来源期刊

Journal of Applied Research and Technology 工程技术-工程：电子与电气

CiteScore

1.50

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Applied Research and Technology (JART) is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research. JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: -Material Science: Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors. -Computer Science: Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering. -Industrial Engineering: Operations research, systems engineering, management science, complex systems and cybernetics applications and information technologies -Electronic Engineering: Solid-state physics, radio engineering, telecommunications, control systems, signal processing, power electronics, electronic devices and circuits and automation. -Instrumentation engineering and science: Measurement devices (pressure, temperature, flow, voltage, frequency etc.), precision engineering, medical devices, instrumentation for education (devices and software), sensor technology, mechatronics and robotics.