One of the IT2FS (interval type-2 fuzzy system) defuzzification methods uses the iterative KM algorithm. Because of the iterative nature of KM-type reduction, it may be a computational bottleneck for the real-time applications of IT2FSs. There are several other interval type-2 defuzzification methods suffering from lack of meaningful relationship between membership function uncertainties and changing of system output due to lack of clearly defined variables related to uncertainty in their methods. In this paper, a new approach for IT2FS defuzzification is presented by reconfiguring interval type-2 fuzzy sets and how uncertainties are present in them. This closed-formula method provides meaningful relation between the presence of uncertainty and its effect on system output. This study investigates uncertainty avoidance that the output of IT2FS obtained by centroid or bisection methods in comparison with type-1 fuzzy system (T1FLS) moves to points with less uncertainty. Uncertainty can enter into T1FSs and affect system response. Finally, for proving the affectivity of the proposed defuzzification method and uncertainty avoidance, several investigations are done and a prototype two-input one-output IT2FS MATLAB code is enclosed.

中文翻译：

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不确定性回避者间隔II型模糊化方法

IT2FS（间隔2型模糊系统）去模糊方法之一是使用迭代KM算法。由于KM类型缩减的迭代性质，它可能是IT2FS实时应用的计算瓶颈。还有其他两种区间2型去模糊方法，由于缺少与方法不确定性相关的明确定义的变量，因此隶属函数不确定性与系统输出变化之间缺乏有意义的关系。在本文中，通过重新配置间隔类型2模糊集以及其中的不确定性，提出了一种IT2FS去模糊化的新方法。这种封闭式方法在不确定性的存在及其对系统输出的影响之间提供了有意义的关系。本研究调查了避免不确定性的方法，即与1类模糊系统（T1FLS）相比，质心或二等分方法获得的IT2FS的输出移动到不确定性较小的点。不确定性可能会进入T1FS，并影响系统响应。最后，为了证明所提出的去模糊方法的有效性和避免不确定性，进行了一些研究，并附带了一个原型二输入一输出IT2FS MATLAB代码。