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The Stratic Defuzzifier for Discretised General Type-2 Fuzzy Sets
Information Sciences Pub Date : 2020-11-21 , DOI: 10.1016/j.ins.2020.10.062
Sarah Greenfield , Francisco Chiclana

Stratification is a feature of the type-reduced set of the general type-2 fuzzy set, from which a new technique for general type-2 defuzzification, Stratic Defuzzification, may be derived. Existing defuzzification strategies are summarised. The stratified structure is described, after which the Stratic Defuzzifier is presented and contrasted experimentally for accuracy and efficiency with both the Exhaustive Method of Defuzzification (to benchmark accuracy) and the α-Planes/Karnik-Mendel Iterative Procedure strategy, employing 5, 11, 21, 51 and 101 α-planes. The Stratic Defuzzifier is shown to be much faster than the Exhaustive Defuzzifier. In fact the Stratic Defuzzifier and the α-Planes/Karnik-Mendel Iterative Procedure Method are comparably speedy; the speed of execution correlates with the number of planes participating in the defuzzification process. The accuracy of the Stratic Defuzzifier is shown to be excellent. It is demonstrated to be more accurate than the α-Planes/Karnik-Mendel Iterative Procedure Method in four of six test cases, regardless of the number of α-planes employed. In one test case, it is less accurate than the α-Planes/Karnik-Mendel Iterative Procedure Method, regardless of the number of α-planes employed. In the remaining test case, the α-Planes/Karnik-Mendel Iterative Procedure Method with 11 α-Planes gives the most accurate result, with the Stratic Defuzzifier coming second.



中文翻译:

离散广义2型模糊集的Stratic Defuzzifier

分层是一般类型2模糊集的类型减少集的一项功能,可以从中得出用于一般类型2模糊化的新技术Stratic Defuzzification。总结了现有的去模糊策略。描述了分层结构,然后展示了Stratic Defuzzifier并通过详尽的Defuzzification方法(达到基准精度)和精确度进行了对比实验,以确保准确性和效率。α-Planes / Karnik-Mendel迭代程序策略,采用5、11、21、51和101 α-飞机。Stratic Defuzzifier显示出比Exhaustive Defuzzifier快得多。实际上Stratic Defuzzifier和α-Planes / Karnik-Mendel迭代过程方法相对较快;执行速度与参与解模糊过程的飞机数量相关。Stratic Defuzzifier的准确性非常好。它被证明比α-在六个测试案例中的四个中,使用Planes / Karnik-Mendel迭代过程方法,而无需考虑 α飞机。在一个测试案例中,它的准确性不如α-Planes / Karnik-Mendel迭代过程方法,无论数量多少 α飞机。在其余的测试用例中,α-Planes / Karnik-Mendel的迭代过程方法,带11 α-Planes提供最准确的结果,而Stratic Defuzzifier排名第二。

更新日期:2020-11-22
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