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A faster iterative computation of the centroid of an interval type-2 fuzzy set

机译:一种更快的迭代计算间隔类型-2模糊集的质心

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This paper presents a new iterative algorithm for computing the centroid of an interval type-2 fuzzy set (also known as interval-valued fuzzy set). The algorithm uses precomputation to speed up its calculations and an initialization based on the concept of uncertainty bounds. Computational experiments over different kind of footprints of uncertainty and several discretization levels show that the new algorithm is much faster than methods such as the Enhanced Karnik-Mendel Algorithm (EKMA) and the Enhanced Iterative Algorithm with Stop Conditon (EIASC).
机译:本文提出了一种用于计算间隔类型2模糊集的质心的新迭代算法(也称为间隔值模糊集)。该算法使用预压缩来加速其计算和基于不确定性范围的概念的计算和初始化。不同类型的不确定性占地面积和几个离散化水平的计算实验表明,新算法比诸如增强型Karnik-Mendel算法(EIASC)和增强型迭代算法等方法的方法快得多。

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