Interpretation of Artificial Neural Networks by Means of Fuzzy Rules  

Oleh:

Benitez, J. M. ; Castro, J. L. ; Mantas, C. J.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 1 (2002), page 101-116.
Topik: NEURAL NETWORKS; interpretation; artificial neural networks; fuzzy rules

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper presents an extension of the method presented by Benitez et al (1997) 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 are in accordance with the domain of the input variables. These rules use a new operator in the antecedent. The properties and 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.

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