模糊粗糙集理论中决策规则集的有效性

IF 2.7 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2025-08-06 DOI:10.1016/j.fss.2025.109548

Fernando Chacón-Gómez, M. Eugenia Cornejo, Jesús Medina

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引用次数: 0

摘要

数据集在（模糊）粗糙集理论中被解释为决策表，以获得有用的信息，例如在决策中使用。这些表是通过一组决策规则来建模的，Pawlak称之为决策算法。用效率的概念对这些算法进行分析，评价它们的分类质量。本文提出了在模糊框架中定义效率概念的两种不同方法。第一种方法是对经典情况的直接推广，而第二种方法则是在保留经典框架哲学的情况下获得有界效率。通过不同的性质和实例说明了这两种方法。

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Efficiency of decision rule sets in fuzzy rough set theory

Datasets have been interpreted in (fuzzy) rough set theory as decision tables to obtain useful information to be used, for example, in decision making. These tables have been modeled through a collection of decision rules, which was called decision algorithm by Pawlak. These algorithms are analyzed by the notion of efficiency, which evaluates their quality of classification. This paper presents two different approaches for defining the notion of efficiency in the fuzzy framework. The first approach is a direct generalization to the classical case, while the second one is focused on obtaining a bounded efficiency preserving the philosophy of the classical framework. Both approaches are illustrated by means of different properties and examples.

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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.