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A u-map representation of general type-2 fuzzy sets via concepts from activation detection: Application to constructing type-2 fuzzy set measures

机译:通用类型2模糊集的u-map表示,其概念来自激活检测:在构建类型2模糊集测度中的应用

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Following the introduction of type-2 fuzzy sets (T2FS) by Zadeh in 1975, the theory of T2FS has been further developed by a series of notable researchers, and it has been widely used in a variety of applications nowadays. While recent theoretical developments have led to simplifications in the theory of T2FS, it can be argued that theoretical difficulties concerning these developments still persist, inhibiting T2FS from reaching its full potential. With this in mind, in this article, we introduce a concept termed the u-map representation of type-2 fuzzy sets, a simple yet powerful tool for T2FS specialists to further develop T2FS theories, and for non-specialists to adapt T2FS for their applications. With the u-map representation, we show that it is extremely simple to translate manipulations involving type-1 fuzzy sets into corresponding manipulations involving type-2 fuzzy sets. This means that a measure for type-1 fuzzy sets could be converted into a corresponding measure for type-2 fuzzy sets in a straightforward and theoretically satisfying manner, overcoming some of the key theoretical difficulties and restrictions of previous approaches. Moreover, we describe a foundational mental model underlying the u-map representation. Such a foundational model empowers one to check the reasonableness of various definitions, propositions, and computation results associated with measures constructed under the u-map representation. We illustrate the utility of the u-map representation and its foundational mental model via the constructions and the interpretations of a T2FS subsethood measure, a T2FS entropy measure, and a T2FS relative entropy measure. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在1975年Zadeh引入类型2模糊集(T2FS)之后,T2FS的理论得到了一系列著名研究人员的进一步发展,并且在当今的各种应用中得到了广泛的应用。尽管最近的理论发展导致T2FS理论的简化,但可以认为与这些发展有关的理论困难仍然存在,从而阻碍了T2FS发挥其全部潜力。考虑到这一点,在本文中,我们介绍了一个称为2型模糊集的u-map表示的概念,它是T2FS专家进一步发展T2FS理论以及非专业人士将T2FS应用于他们的简单而强大的工具应用程序。使用u-map表示,我们表明将涉及类型1模糊集的操作转换为涉及类型2模糊集的相应操作非常简单。这意味着可以以一种简单且理论上令人满意的方式将用于类型1模糊集的度量转换为用于类型2模糊集的相应度量,从而克服了先前方法的一些关键的理论困难和限制。此外,我们描述了基于u-map表示的基础心理模型。这种基础模型使人们能够检查与在u-map表示下构造的度量相关的各种定义,命题和计算结果的合理性。我们通过T2FS子集测度,T2FS熵测度和T2FS相对熵测度的构造和解释,说明了u-map表示及其基础心理模型的实用性。 (C)2016 Elsevier Ltd.保留所有权利。

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