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Towards an Operational Interpretation of Membership Grades - On H-Valued Fuzzy Sets and Their Use for Fuzzy Quantification

机译:朝向成员级的运作解释 - 关于H值模糊集及其对模糊量化的用途

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Advances in fuzzy quantification have rendered possible a consistent interpretation of quantifying expressions involving vague quantifiers and fuzzy arguments (Glockner 2006, Diaz-Hermida et al 2005). However, the assumption of these approaches that the modeller is able to specify precise [0,1]-valued membership functions for the involved fuzzy sets and fuzzy quantifiers can be too strong in certain cases. To alleviate this problem, we extend the existing theory of fuzzy quantification to lattice-valued fuzzy sets which no longer require a specification of precise numerical membership grades. The paper focuses on a special type of so called H-lattices whose Hasse diagram has an hourglass shape. In this setting, we can achieve an operational interpretation of membership values, which can be calculated automatically provided that the modeller (a) decides on the basic tendency of the membership assessments and (b) specifies the salient ordering relationships between the confidence levels. The generalization of the existing theory of fuzzy quantification to H-valued fuzzy sets is a straightforward task and few properties of the models will be lost when turning from [0,1] to the generalized valuations. It is even possible to devise a generic construction which assigns a plausible model of fuzzy quantification to any given H-lattice
机译:模糊量化的进步使得对涉及模糊量词和模糊争论的量化表达式的一致解释(Glockner 2006,Diaz-Hermida等人2005)。然而,这些方法的假设使得莫德勒能够指定精确的[0,1] - 所涉及的模糊集和模糊量子的隶属函数在某些情况下可能太强烈。为了减轻这个问题,我们将现有的模糊量化理论扩展到格子值的模糊集,这些模糊集,不再需要精确的数值隶属等级的规范。该文件侧重于特殊类型的所谓的H格子,其脊状图具有沙漏形状。在此设置中,我们可以实现会员资格值的操作解释,可以自动计算,即Modeller(a)决定成员评估的基本趋势,并且(b)指定置信水平之间的突出条件关系。现有的模糊量化理论对H值模糊集的概括是一个直截了当的任务,从从[01]转向广义估值时,模型的几个属性将丢失。甚至可以设计一种通用结构,该仿制结构为任何给定的H格子分配了一种模糊量化的合理模型

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