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Fast and accurate center of gravity defuzzification of fuzzy system outputs defined on trapezoidal fuzzy partitions

机译:在梯形模糊分区上定义的模糊系统输出的快速准确的重心去模糊化

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摘要

In this article three methods are presented to perform the center of gravity (COG) defuzzification method in the context of linguistic fuzzy models with t-norm-based inference: one well-known method, the discretisation method, and two new methods, the slope-based method and the modified transformation function method. The methods are worked out for trapezoidal membership functions forming a fuzzy partition in the sense of Ruspini. Experimental results show that the newly introduced methods exhibit excellent accuracy at an extremely low computational cost compared to the widely applied discretisation method.
机译:本文介绍了三种基于t范数推理的语言模糊模型来执行重心(COG)去模糊方法的方法:一种著名的方法,离散化方法,以及两种新的方法,斜率的方法和改进的变换函数方法。研究了梯形隶属函数的方法,形成了Ruspini意义上的模糊分区。实验结果表明,与广泛应用的离散化方法相比,新引入的方法以极低的计算成本表现出优异的准确性。

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