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A membership function selection method for fuzzy neural networks
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A membership function selection method for fuzzy neural networks

Qing Qing Zhou, Martin Purvis and Nikola Kasabov
12/1997
Handle:
https://hdl.handle.net/10523/1027

Abstract

Knowledge Engineering Laboratory QA76 Computer software
Fuzzy neural networks provide for the extraction of fuzzy rules from artificial neural network architectures. In this paper we describe a general method, based on statistical analysis of the training data, for the selection of fuzzy membership functions to be used in connection with fuzzy neural networks. The technique is first described and then illustrated by means of two experimental examinations.
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