蜂群优化的第 3 类模糊动态适应应用于数学函数

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2024-05-21 DOI:10.1016/j.fss.2024.109014

Leticia Amador-Angulo , Oscar Castillo , Patricia Melin , Zong Woo Geem

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引用次数: 0

摘要

本文概述了一种用于提高蜂群优化（BCO）性能的区间-3 型模糊逻辑系统（IT3FLS）。在一组基准数学函数上的结果验证了 IT3FLS 方法的效率。IT3FLS 提供的方法有助于确定 α 和 β 参数的最佳值，从而提高原始 BCO 的性能。IT3FLS 方法在优化基准函数方面具有优势。可以看出，IT3FLS 在数学函数集的最小值方面表现出更好的效果。实验表明，与使用通用 2 型 FLS（GT2FLS）、区间 2 型 FLS（IT2FLS）和 1 型 FLS（T1FLS）的变体相比，IT3FLS 方法的实施提高了 BCO 的性能。

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Type-3 fuzzy dynamic adaptation of Bee colony optimization applied to mathematical functions

In this article, an Interval Type-3 Fuzzy Logic System (IT3FLS) for enhancing the performance in Bee Colony Optimization (BCO) is outlined. The efficiency of the IT3FLS approach is verified with results on a set of benchmark mathematical functions. The IT3FLS provides an approach that helps to identify the optimal values in $α$ and $β$ parameters that allows to improve the performance in the original BCO. The IT3FLS approach exhibits advantages in the optimization of the benchmark functions. It can be noted that a IT3FLS exhibits better results in the minimal values of the set of mathematical functions. The experimentation demostrates that the implementation of the IT3FLS approach enhances the performance of BCO when compared with respect to the variants utilizing Generalized Type-2 FLS (GT2FLS), Interval Type-2 FLS (IT2FLS) and Type-1 FLS (T1FLS).

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来源期刊

Fuzzy Sets and Systems 数学-计算机：理论方法

CiteScore

6.50

自引率

17.90%

发文量

321

审稿时长

6.1 months

期刊介绍： Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.