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A method for automatic construction of a fuzzy expert system from numerical data using the ILFN network and a genetic algorithm is presented. The incremental learning fuzzy neural (ILFN) network was developed for pattern classification problems. The ILFN network is a fast, one-pass, on-line, and incremental learning algorithm. A knowledge base for fuzzy expert systems is extracted from the hidden units of the ILFN classifier. The genetic algorithm is then used, in an iterative manner, to reduce the number of rules and select important input pattern features needed to generate a comprehensible fuzzy rule-based system
Published in:
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
(Volume:3
)
Date of Conference: 2000
- Page(s):
- 1917 - 1922 vol.3
- Meeting Date :
- 08 Oct 2000-11 Oct 2000
- ISSN :
- 1062-922X
- Print ISBN:
- 0-7803-6583-6
- INSPEC Accession Number:
- 6771540
- Conference Location :
- Nashville, TN
- Digital Object Identifier :
- 10.1109/ICSMC.2000.886393
- Product Type:
- Conference Publications
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