A generic fuzzy aggregation operator: rules extraction from and insertion into artificial neural networks |
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Authors: | C J Mantas |
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Affiliation: | (1) Department of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain |
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Abstract: | Multilayered feedforward artificial neural networks (ANNs) are black boxes. Several methods have been published to extract
a fuzzy system from a network, where the input–output mapping of the fuzzy system is equivalent to the mapping of the ANN.
These methods are generalized by means of a new fuzzy aggregation operator. It is defined by using the activation function
of a network. This fact lets to choose among several standard aggregation operators. A method to extract fuzzy rules from
ANNs is presented by using this new operator. The insertion of fuzzy knowledge with linguistic hedges into an ANN is also
defined thanks to this operator. |
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Keywords: | Fuzzy aggregation Artificial neural networks Additive fuzzy systems |
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