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HyFOM Reasoner: Hybrid Integration of Fuzzy Ontology and Mamdani Reasoning

机译:HYFOM推理:模糊本体和Mamdani推理的混合集成

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Some real-world applications require representation and reasoning regarding imprecise or vague information. In this context, the appropriate combination of fuzzy ontologies and Mamdani fuzzy inference systems can provide meaningful inferences involving fuzzy rules and numerical property values. In general, this knowledge is not obtained through typical fuzzy ontology reasoning and can be relevant for some ontology reasoning tasks that depend on numerical property values. To address this issue, this paper proposes the HyFOM reasoner, which provides a hybrid integration of fuzzy ontology and Mamdani reasoning. A real-world case study involving the domain of food safety is presented, including comparative results with a state-of-the-art fuzzy description logic reasoner.
机译:一些现实世界应用程序需要关于不精确或模糊信息的表示和推理。在这种情况下,模糊本体和Mamdani模糊推理系统的适当组合可以提供有意义的推论,涉及模糊规则和数值值。通常,通过典型的模糊本体学推理,无法获得此知识,并且可以与某些依赖于数值值的本体推理任务相关。为了解决这个问题,本文提出了Hyfom推理,它提供了模糊本体和Mamdani推理的混合集成。提出了涉及食品安全领域的真实案例研究,包括具有最先进的模糊描述逻辑推理的对比结果。

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