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
“…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).…”
Purpose: The objective of the research is proposed a methodology to prepare a Zero-Based Budget (ZBB) for Small and Medium-sized Enterprises (SMEs) in Ecuador, applying fuzzy logic. Design/methodology/approach: A quantitative approach is assumed to show findings derived from the work carried out in these Ecuadorian business units, belonging to non-essential sectors such as wood, textiles and footwear. Fuzzy logic, the technique of expertise, and Trapezoidal Fuzzy Numbers (TpFN) are used to capture true budget levels. Findings: The results recommend that optimal budget levels can be obtained for SMEs in restrictive and health emergency contexts. Originality/value: As a result of COVID-19 pandemic, markets and demand are contracting causing variations in income and demanding greater rationalization at the level of expenditures. For SMEs is essential prepared income and disbursements estimates. Based on the methodology proposed, predictions are made to achieve the objectives of SMEs. Directors will be able to make more successful decisions for the benefit of their companies, to streamline operations, direct the achievement of objectives, rationalize expenses (costs and expenses), and to project better scenarios in the future before carrying out cost-benefit analysis.
“…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).…”
Purpose: The objective of the research is proposed a methodology to prepare a Zero-Based Budget (ZBB) for Small and Medium-sized Enterprises (SMEs) in Ecuador, applying fuzzy logic. Design/methodology/approach: A quantitative approach is assumed to show findings derived from the work carried out in these Ecuadorian business units, belonging to non-essential sectors such as wood, textiles and footwear. Fuzzy logic, the technique of expertise, and Trapezoidal Fuzzy Numbers (TpFN) are used to capture true budget levels. Findings: The results recommend that optimal budget levels can be obtained for SMEs in restrictive and health emergency contexts. Originality/value: As a result of COVID-19 pandemic, markets and demand are contracting causing variations in income and demanding greater rationalization at the level of expenditures. For SMEs is essential prepared income and disbursements estimates. Based on the methodology proposed, predictions are made to achieve the objectives of SMEs. Directors will be able to make more successful decisions for the benefit of their companies, to streamline operations, direct the achievement of objectives, rationalize expenses (costs and expenses), and to project better scenarios in the future before carrying out cost-benefit analysis.
“…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.…”
In Rough Set Theory, the notion of bireduct allows to simultaneously reduce the sets of objects and attributes contained in a dataset. In addition, value reducts are used to remove some unnecessary values of certain attributes for a specific object. Therefore, the combination of both notions provides a higher reduction of unnecessary data. This paper is focused on the study of bireducts and value reducts of information and decision tables. We present theoretical results capturing different aspects about the relationship between bireducts and reducts, offering new insights at a conceptual level. We also analyze the relationship between bireducts and value reducts. The studied connections among these notions provide important profits for the efficient information analysis, as well as for the detection of unnecessary or redundant information.
“…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).…”
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