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2021
DOI: 10.1002/mma.7470
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A measure of consistency for fuzzy logic theories

Abstract: Fuzzy logic has shown to be a suitable framework to handle contradictions in which, unsurprisingly, the notion of inconsistency can be defined in different ways. This paper starts with a short survey of different ways to define the notion of inconsistency in fuzzy logic systems. As a result, we provide a first notion of inconsistency by means of the absence of models. Subsequently, we define two measures of consistency that belong purely to the fuzzy paradigm; in the sense that both measures coincide with the … Show more

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Cited by 5 publications
(4 citation statements)
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References 27 publications
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“…Fuzzy logic handles imprecise information, in terms of fuzzy sets that are combined in rules to define actions; it relies on mathematical models to provide answers that help to face decision problems in the field of business activity (Muñoz et al, 2016). It uses novel techniques that support the adequate treatment of uncertainty such as confidence intervals, confidence triples, fuzzy subsets and experts (Casanovas and Fernández, 2003) and maintains as a premise that fuzzy concepts derive from fuzzy phenomena that commonly occur in the real world (Kantardzic, 2019), proving to be an adequate framework to handle contradictions (Madrid and Ojeda-Aciego, 2021).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Fuzzy logic handles imprecise information, in terms of fuzzy sets that are combined in rules to define actions; it relies on mathematical models to provide answers that help to face decision problems in the field of business activity (Muñoz et al, 2016). It uses novel techniques that support the adequate treatment of uncertainty such as confidence intervals, confidence triples, fuzzy subsets and experts (Casanovas and Fernández, 2003) and maintains as a premise that fuzzy concepts derive from fuzzy phenomena that commonly occur in the real world (Kantardzic, 2019), proving to be an adequate framework to handle contradictions (Madrid and Ojeda-Aciego, 2021).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, we will study the generalization of the results introduced in this paper to the fuzzy environment. Furthermore, we will analyze more relationships between bireducts and value reducts, and their relation and application to other frameworks, such as logic, formal concept analysis and non‐linear relation equations 16,27–29 . In particular, we are also interested in the study of the relationship between decision rules and attribute implication, studied in formal concept analysis.…”
Section: Conclusion and Further Workmentioning
confidence: 99%
“…Intelligent control is divided into two branches: control by neural networks and fuzzy logic control. Neural network conducts the analysis through a historical database; using weighted connections between neurons for activation functions, it learns complex patterns and achieves effective control without requiring an understanding of the internal dynamics of the plant, considering it as "black box," focusing attention only on the input and output characteristics (Madrid & Ojeda-Aciego, 2021).…”
mentioning
confidence: 99%