设计简约区间2型模糊逻辑系统的新2型规则排序指标

Shang-Ming Zhou, R. John, F. Chiclana, J. Garibaldi
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引用次数: 6

摘要

本文提出了2型模糊规则排序的两个新指标,以识别在2型模糊逻辑系统设计中最具影响力的模糊规则,并将其分别命名为模糊规则的r值和c值。2型模糊规则的r值是通过QR分解得到的,其中不需要用列旋转算法估计SVD-QR所要求的秩。建议采用二类模糊规则的c值,根据规则结果的效果对规则进行排序。一个信号恢复问题的实验结果表明,在保证系统性能的前提下,利用所提出的指标可以有效地选择影响最大的2型模糊规则来构建简洁的2型模糊模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Type-2 Rule Ranking Indices for Designing Parsimonious Interval Type-2 Fuzzy Logic Systems
In this paper, we propose two novel indices for type-2 fuzzy rule ranking to identify the most influential fuzzy rules in designing type-2 fuzzy logic systems, and name them as R-values and c-values of fuzzy rules separately. The R-values of type-2 fuzzy rules are obtained by applying QR decomposition in which there is no need to estimate a rank as required in the SVD-QR with column pivoting algorithm. The c-values of type-2 fuzzy rules are suggested to rank rules based on the effects of rule consequents. Experimental results on a signal recovery problem have shown that by using the proposed indices the most influential type-2 fuzzy rules can be effectively selected to construct parsimonious type-2 fuzzy models while the system performances are kept at a satisfied level.
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