...
首页> 外文期刊>International Journal of Fuzzy Systems >Discrete Non-iterative Centroid Type-Reduction Algorithms on General Type-2 Fuzzy Logic Systems
【24h】

Discrete Non-iterative Centroid Type-Reduction Algorithms on General Type-2 Fuzzy Logic Systems

机译:一般类型-2模糊逻辑系统上的离散非迭代质心型算法

获取原文
获取原文并翻译 | 示例
           

摘要

Since the alpha-planes expressions of general type-2 fuzzy sets (GT2 FSs) have been proposed, general type-2 fuzzy logic systems (GT2 FLSs) that are dependent on GT2 FSs are becoming quite popular to fuzzy logic researchers. Usually enhanced Karnik-Mendel (EKM) algorithms are adopted for performing the kernel block of type-reduction (TR). However, the essence of EKM-based TR process probably hinders the GT2 FLSs from real-world applications. It is an intriguing as well as unsolved problem for comparing EKM algorithms with other non-iterative algorithms. This paper provides a framework encompassing fuzzy reasoning, defuzzification, as well as type-reduction. Furthermore, the continuous of NT (CNT) algorithm is shown to be a precise approach when it is used to execute the centroid TR of GT2 fuzzy logic systems. Four computer tests display the characteristics of discrete Nagar-Bardini (NB) and Nie-Tan (NT) non-iterative algorithms. Compared with EKM approach, the developed one exhibits some superiorities in terms of guaranteeing high computation accuracy and low computation burdens, which broadens the application ranges for the proposed method.
机译:由于已经提出了一般类型-2模糊集(GT2 FSS)的alpha-Planes表达式,因此依赖于GT2 FSS的一般类型-2模糊逻辑系统(GT2FLS)正变得非常受欢迎到模糊逻辑研究人员。通常采用增强的Karnik-Mendel(EKM)算法用于执行缩减类型(TR)的内核块。然而,基于EKM的TR过程的本质可能会阻碍来自现实世界的GT2媒体。将EKM算法与其他非迭代算法进行比较是一种有趣的还是未解决的问题。本文提供了一种包含模糊推理,排出的框架以及减少型框架。此外,当用于执行GT2模糊逻辑系统的质心TR时,将显示NT(CNT)算法的连续方法是一种精确的方法。四台计算机测试显示离散Nagar-Bardini(NB)和NIE-TAN(NT)非迭代算法的特征。与EKM的方法相比,开发的展示了一些优势,以保证高计算精度和低计算负担,这拓宽了所提出的方法的应用范围。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号