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On transitioning from type-1 to interval type-2 fuzzy logic systems

机译:从1型过渡到区间2型模糊逻辑系统

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Capturing the uncertainty arising from system noise has been a core feature of fuzzy logic systems (FLSs) for many years. This paper builds on previous work and explores the methodological transition of type-1 (T1) to interval type-2 fuzzy sets (IT2 FSs) for given “levels” of uncertainty. Specifically, we propose to transition from T1 to IT2 FLSs through varying the size of the Footprint Of Uncertainty (FOU) of their respective FSs while maintaining the original FS shape (e.g., triangular) and keeping the size of the FOU over the FS as constant as possible. The latter is important as it enables the systematic relating of FOU size to levels of uncertainty and vice versa, while the former enables an intuitive comparison between the T1 and T2 FSs. The effectiveness of the proposed method is demonstrated through a series of experiments using the well-known Mackey-Glass (MG) time series prediction problem. The results are compared with the results of the IT2 FS creation method introduced in [1] which follows a similar methodology as the proposed approach but does not maintain the membership function (MF) shape.
机译:多年来,捕获由系统噪声引起的不确定性一直是模糊逻辑系统(FLS)的核心特征。本文以先前的工作为基础,并探讨了在给定的“不确定性”水平下,从类型1(T1)过渡到区间类型2模糊集(IT2 FS)的方法学转变。具体来说,我们建议通过更改各自FS的不确定性足迹(FOU)的大小,从T1 FLS过渡到IT2 FLS,同时保持原始FS形状(例如三角形),并保持FS上FOU的大小不变尽可能。后者很重要,因为它可以将FOU大小与不确定性水平进行系统的关联,反之亦然,而前者则可以在T1和T2 FS之间进行直观的比较。通过使用众所周知的Mackey-Glass(MG)时间序列预测问题的一系列实验,证明了该方法的有效性。将结果与[1]中介绍的IT2 FS创建方法的结果进行比较,该方法遵循与所建议的方法类似的方法,但是不保持隶属函数(MF)的形状。

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