Interpretation of artificial neural networks by means of fuzzy rules

被引：83

作者：

Castro, JL ^{[1
]}

Mantas, CJ ^{[1
]}

Benítez, JM ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, E-18071 Granada, Spain

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2002年 / 13卷 / 01期

关键词：

artificial neural networks (ANNs); extraction; fuzzy rules; interpretation;

D O I：

10.1109/72.977279

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an extension of the method presented by Benitez et al. for extracting fuzzy rules from an artificial neural network (ANN) that express exactly its behavior. The extraction process provides an interpretation of the ANN in terms of fuzzy rules. The fuzzy rules presented in this paper are in accordance with the domain of the input variables. These rules use a new operator in the antecedent. The properties and the intuitive meaning of this operator are studied. Next, the role of the biases in the fuzzy rule-based systems is analyzed. Several examples are presented to comment on the obtained fuzzy rule-based systems. Finally, the interpretation of ANNs with two or more hidden layers is also studied.

引用

页码：101 / 116

页数：16

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