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Fuzzy rule extraction from a trained multilayer neural network

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2 Author(s)
Matthews, C. ; Dept. of Inf. Technol., La Trobe Univ., Bendigo, Vic., Australia ; Jagielska, I.

This paper focuses on one half of the knowledge acquisition problem for fuzzy systems, namely the acquisition of a fuzzy rule base from a set of input/output data, and in particular on the extraction of a set of fuzzy rules from a trained neural network. Some limitations with previously reported work in this area are first identified. Two simple rule extraction techniques are then described and tested on a well known classification problem. The performance of the resultant rule bases compares more favourably than those reported using alternative techniques

Published in:

Neural Networks, 1995. Proceedings., IEEE International Conference on  (Volume:2 )

Date of Conference:

Nov/Dec 1995

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