Effect of different initializations on EKM algorithm

Syed Moshfeq Salaken, A. Khosravi, S. Nahavandi, Dongrui Wu
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引用次数: 3

Abstract

As an integral part of interval type-2 fuzzy logic system (IT2FLS), type reduction (TR) plays a vital role in determining the performance of IT2FLS. Out of many type reduction algorithms, only Karnik-Mendel type TR algorithms capture the essence of interval type-2 fuzzy sets in type reduction. Enhanced Karnik-Mendel (EKM) algorithm is the most commonly used TR algorithm. In this work, we propose three new initializations for EKM algorithm. It is shown they are performing better than EKM and one of the proposed initializations significantly outperforms others. The performance gain can be upto 40% as per comprehensive simulation results demonstrated in this paper. Our findings are justified by computational time savings and iteration requirement for switch point search.
不同初始化对EKM算法的影响
类型约简(TR)作为区间2型模糊逻辑系统(IT2FLS)的组成部分,在决定区间2型模糊逻辑系统性能方面起着至关重要的作用。在众多类型约简算法中,只有Karnik-Mendel型TR算法抓住了区间2型模糊集在类型约简中的本质。增强型Karnik-Mendel (EKM)算法是最常用的TR算法。在这项工作中,我们提出了三种新的初始化EKM算法。结果表明,它们的性能优于EKM,其中一种建议的初始化明显优于其他初始化。综合仿真结果表明,性能增益可达40%。我们的发现是合理的计算时间节省和迭代要求的切换点搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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