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Fuzzistics for interval type-2 fuzzy sets using centroid as measure of uncertainty

机译:基于质心作为不确定性度量的区间2型模糊集的模糊学

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How to design an interval type-2 fuzzy set (IT2 FS) from data has been a challenging issue till now. Mendel pointed that the centroid of an IT2 FS may be used as a measure of uncertainty to constraint its footprint of uncertainty (FOU) [1]. How to exact centroid from data has been studied in [1]; however, there exists no method to design an IT2 FS such that its centroid matches the desired one. To fill this gap, this paper will present an approach to obtain FOU parameters of an IT2 FS such that its centroid equals to the desired one. To propose this approach, the centroid requirement was formulated as two equations about all the FOU parameters. The strategy used to obtain FOU parameters satisfying the established equations is to predetermine all the FOU parameters except two of them so that these the established equations can be simplified to two single-variable equations. Then the other two FOU parameters can be obtained by solving these two single-variable equations. Among existing root-finding algorithms, false position algorithm is recommended to solve the established single-variable equations. The overall merits of the proposed approach is its simplicity in the implementation, but also its applicability to an IT2 FS with arbitrary shapes of FOU. In addition, numerical examples are provided to further illustrate how to use the proposed approach to obtain the FOU parameters of an IT2 FS.
机译:迄今为止,如何从数据设计间隔2型模糊集(IT2 FS)一直是一个具有挑战性的问题。孟德尔指出,IT2 FS的质心可以用作不确定性的量度,以限制其不确定性(FOU)的覆盖范围[1]。在[1]中已经研究了如何从数据中确定质心。但是,没有一种方法可以设计IT2 FS使其质心与所需的质心匹配。为了填补这一空白,本文将介绍一种获取IT2 FS的FOU参数的方法,以使其质心等于所需的质心。为了提出这种方法,质心要求被公式化为关于所有FOU参数的两个方程。用于获得满足已建立方程式的FOU参数的策略是预先确定除其中两个之外的所有FOU参数,以便将这些已建立方程式简化为两个单变量方程式。然后可以通过求解这两个单变量方程来获得其他两个FOU参数。在现有的寻根算法中,建议使用假位置算法来求解已建立的单变量方程。提议的方法的总体优点是它的实现简单,而且还适用于具有任意形状的FOU的IT2 FS。另外,提供了数字示例以进一步说明如何使用所提出的方法来获取IT2 FS的FOU参数。

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