Population Diversity Management of Swallow Swarm Optimization Algorithm for Fuzzy Classification Problem

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2024-07-22 DOI:10.3103/s0005105524700110

I. A. Hodashinsky

引用次数: 0

Abstract

In swarm algorithms, the need to measure population diversity arises in various contexts, such as in the adaptation of algorithm parameters, preventing the premature convergence of the algorithm and stopping and restarting it. Measures of population diversity allow the phases of the algorithm, namely, diversification and intensification, to be controlled. The article experimentally investigated six measures of population diversity of the optimization of the swallow swarm algorithm when solving the problem of optimizing the parameters of the membership functions of fuzzy classifiers. The resulting classifiers were tested on publicly available data sets drawn from the KEEL repository.

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用于模糊分类问题的燕群优化算法的种群多样性管理

摘要在蜂群算法中，需要在各种情况下测量种群多样性，如适应算法参数、防止算法过早收敛以及停止和重新启动算法。种群多样性的测量可以控制算法的阶段，即多样化和集约化。在解决模糊分类器成员函数参数优化问题时，文章对燕子群算法优化的六种种群多样性措施进行了实验研究。由此产生的分类器在 KEEL 数据库中的公开数据集上进行了测试。

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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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.