DISTRIBUTED REPRESENTATION OF FUZZY RULES AND ITS APPLICATION TO PATTERN-CLASSIFICATION

被引：331

作者：

ISHIBUCHI, H

NOZAKI, K

TANAKA, H

机构：

[1] Department of Industrial Engineering, University of Osaka Prefecture, Osaka

来源：

FUZZY SETS AND SYSTEMS | 1992年 / 52卷 / 01期

关键词：

DISTRIBUTED FUZZY RULES; DISTRIBUTED REPRESENTATION; FUZZY INFERENCE; GENERATION OF FUZZY RULES; PATTERN CLASSIFICATION;

D O I：

10.1016/0165-0114(92)90032-Y

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper introduces the concept of distributed representation of fuzzy rules and applies it to classification problems. Distributed representation is implemented by superimposing many fuzzy rules corresponding to different fuzzy partitions of a pattern space. This means that we simultaneously employ many fuzzy rule tables corresponding to different fuzzy partitions in fuzzy inference. In order to apply distributed representation of fuzzy rules to pattern classification problems, we first propose an algorithm to generate fuzzy rules from numerical data. Next we propose a fuzzy inference method using the generated fuzzy rules. The classification power of distributed representation is compared with that of ordinary fuzzy rules which can be viewed as local representation.

引用

页码：21 / 32

页数：12

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