不完全数据下可解释层次模糊系统的构造

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

Fuzzy Sets and Systems Pub Date : 2025-01-09 DOI:10.1016/j.fss.2025.109273

Changle Sun , Haitao Li , Jun-e Feng

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引用次数: 0

摘要

层次模糊系统是模糊系统的一个重要分支。本文研究了可解释hfs的代数表达式，提出了两种基于不完备数据的可解释hfs的构造算法。首先，提出了可解释模糊逻辑单元，并利用矩阵的半张量积建立了可解释模糊逻辑单元的代数表达式。其次，将可解释的目标单元代入层次结构，得到可解释的目标单元。第三，基于近端策略优化，建立了直接算法和间接算法，构建了不完全投入产出数据下的可解释hfs。最后，以高速公路入口匝道计量为例，验证了所得结果的有效性。

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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Construction of interpretable hierarchical fuzzy systems subject to incomplete data

Hierarchical fuzzy systems (HFSs) are a significant branch of fuzzy systems. In this paper, the algebraic formulation of interpretable HFSs is investigated, and two algorithms are developed for the construction of interpretable HFSs subject to incomplete data. Firstly, the interpretable fuzzy logic unit (FLU) is presented and its algebraic formulation is developed by using the semi-tensor product of matrices. Secondly, by substituting the interpretable FLUs into the hierarchical structure, the interpretable HFSs are obtained. Thirdly, based on the proximal policy optimization, both direct and indirect algorithms are established to construct the interpretable HFSs subject to incomplete input-output data. Finally, the effectiveness of obtained results is verified by the on-ramp metering of freeway.

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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.