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Conceptual fuzzy sets and their connectives

机译:概念模糊集及其连接词

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The evacuation of element pertinence to sets and connecting the sets thenmselves when these are not crisp may cause serious epistemological and practical problems. Fuzzy Set Theory (FST) solved some of these problems, with noticeable success since its inception by Zadeh [40] in the 1960s. But that theory now is meeting with difficulties for penetrating AI or, more generally, Cognitive Science. This is mainly due to the characteristics of the membership (characteristic) function and, by reflection, of the connectives MIN-MAX. According to these operators, set connections are performed by diffusing numerical data, i.e. values of membership degree, rather than qualitative data, such as meaning of the data themselves [42], so that the meaning itself can be taken into considerate. In this paper we present an interpretation of element pertinence to sets which yields a more adequate type of set connectives [3].
机译:疏散与集合相关的元素并在不脆的情况下连接集合本身可能会导致严重的认识论和实践问题。模糊集理论(FST)解决了其中的一些问题,自Zadeh [40]在1960年代提出以来,就取得了显著成功。但是,该理论现在在渗透AI或更普遍的认知科学方面遇到了困难。这主要是由于隶属度(特性)函数的特征以及连接词MIN-MAX的反映。根据这些运算符,通过散布数值数据(即隶属度的值)而不是定性数据(例如数据本身的含义)来执行设置连接[42],以便可以考虑含义本身。在本文中,我们对元素与集合的相关性进行了解释,从而产生了更充分类型的集合连接词[3]。

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