基于模糊关联规则的多目标遗传模糊规则选择

2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS) Pub Date : 2013-04-16 DOI:10.1109/GEFS.2013.6601056

Y. Nojima, H. Ishibuchi

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引用次数: 10

摘要

遗传模糊规则选择是一种常用的基于模糊规则的分类器设计方法。在文献中也提出了它的一些变体。在许多关于遗传模糊规则选择的研究中，模糊规则中的每一个先决条件都是针对“x1小”、“x2大”等单一输入变量给出的。因此，每个前因模糊集都是在单个输入变量上定义的。在本文中，我们研究了关于两个输入变量之间的关系的模糊关系条件的使用，例如“x1近似等于x2”和“x3近似大于x4”。这种模糊关系条件由一对输入变量上的模糊集来定义。研究了模糊规则对多目标遗传模糊规则选择设计的模糊规则分类器性能的影响。

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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Multiobjective genetic fuzzy rule selection with fuzzy relational rules

Genetic fuzzy rule selection has been frequently used for fuzzy rule-based classifier design. A number of its variants have also been proposed in the literature. In many studies on genetic fuzzy rule selection, each antecedent condition in fuzzy rules is given for a single input variable such as “x₁ is small” and “x₂ is large”. As a result, each antecedent fuzzy set is defined on a single input variable. In this paper, we examine the use of fuzzy relational conditions with respect to the relation between two input variables such as “x₁ is approximately equal to x₂” and “x₃ is approximately larger than x₄”. Such a fuzzy relational condition is defined by a fuzzy set on a pair of input variables. We examine the effect of using fuzzy rules with fuzzy relational conditions on the performance of fuzzy rule-based classifiers designed by multiobjective genetic fuzzy rule selection.

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2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS)

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