Inference mechanism based on ordered fuzzy rules

被引：1

作者：

Rudnik, Katarzyna ^{[1
]}

Chwastyk, Anna ^{[1
]}

机构：

[1] Opole Univ Technol, Fac Prod Engn & Logist, Opole, Poland

来源：

2023 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ | 2023年

关键词：

ordered fuzzy number; ordered fuzzy rules; uncertainty modeling; fuzzy inference; fuzzy reasoning; supplier assessment;

D O I：

10.1109/FUZZ52849.2023.10309682

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper develops the concept of an inference method for IF-THEN rules with Ordered Fuzzy Numbers (OFNs), called ordered fuzzy rules. These rules allow one to present knowledge in the understandable form of fuzzy rules, which contains additional information about the tendencies of variables' value changes in time. This paper elaborates on an approach to the inference process that is sensitive to the direction of triangular OFNs. This research is the foundation of the creation of a new tool for decision-making in an uncertain environment in the context of rapidly changing data. In the paper, the approach is described based on the example of a managerial problem in the field of supplier evaluation.

引用

页数：6

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