A Survey on Genetic Fuzzy Systems

IF 9.7 2区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Archives of Computational Methods in Engineering Pub Date : 2024-06-27 DOI:10.1007/s11831-024-10157-9

Mohammad Jahani Moghaddam

引用次数: 0

Abstract

Fuzzy Systems have shown their ability for solving a wide range of problems in different application domains. Genetic Algorithms are applied to provide the learning and adaptation capabilities for designing fuzzy systems, and this composition is called genetic fuzzy systems (GFSs). This paper reviews the field of GFSs consisting of the pioneer articles, the most cited papers, GFS milestones, recent research trends and, future outlooks. Additionally, there is paid attention to a short discussion on some critical considerations of recent developments and suggestions for potential future research directions.

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遗传模糊系统概览

模糊系统在解决不同应用领域的广泛问题方面已显示出其能力。遗传算法的应用为设计模糊系统提供了学习和适应能力，这种组合被称为遗传模糊系统（GFSs）。本文回顾了遗传模糊系统领域的先驱文章、被引用次数最多的论文、遗传模糊系统的里程碑、近期研究趋势和未来展望。此外，本文还简要讨论了近期发展的一些关键因素以及对未来潜在研究方向的建议。

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

Archives of Computational Methods in Engineering 工程技术-工程：综合

CiteScore

19.80

自引率

4.10%

发文量

153

审稿时长

>12 weeks

期刊介绍： Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.