基于离散度及果蝇算法的关键节点识别算法  

Key node identification algorithm based on dispersion and fruit fly algorithm

作　　者：付立东[1] 李东洋 FU Li-dong;LI Dong-yang(School of Computer Science and Technology,Xi’an University of Science and Technology,Xi’an 710699,China)

机构地区：[1]西安科技大学计算机科学与技术学院,陕西西安710699

出　　处：《计算机工程与设计》2025年第3期648-656,共9页Computer Engineering and Design

基　　金：国家自然科学基金项目(12071367、61772394);陕西省自然科学基础研究计划基金项目(2020JM-526、2023-JC-YB-517)。

摘　　要：针对现有算法在复杂网络中筛选出的关键节点过于密集、传播效率低的富人俱乐部(Rich-Club)现象,提出一种基于离散度及果蝇算法的关键节点识别算法。利用去除筛选网络中最大影响力节点,网络的流通性将会有最大程度损坏这一特性,定义离散度函数,采用香农熵对果蝇算法进行改进并优化,确定网络最优种子集。在多种类型规模网络上的实验结果表明,该方法能够有效识别复杂网络中具有传播范围更广的最大影响力节点。Aiming at the phenomenon of Rich-Club that the seed nodes screened out by the existing algorithm are too dense and the propagation efficiency is low,the key node identification algorithm based on dispersion and fruit fly algorithm was proposed.The property that the network circulation will be damaged to the greatest extent by removing the most influential nodes in the screening network was used,the node dispersion function was defined,and Shannon entropy was used to improve and optimize the fruit fly algorithm to determine the optimal seed set of the network.Results of experiments on various types of large-scale networks show that the proposed method can effectively identify the most influential nodes with wider propagation in complex networks.

关 键 词：复杂网络 最大影响力节点 果蝇算法 离散度 香农熵 流通性 富人俱乐部 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]