Assessment of EFuNN accuracy for pattern recognition using data with different statistical distributions

Ronei Marcos de Moraes

This work assesses the accuracy of Evolving Fuzzy Neural Networks (EFuNNs) for pattern recognition tasks using seven different statistical distributions data. The recently proposed EFuNNs are dynamic connectionist feed forward networks with five layers of neurons and they are adaptive rule-based systems. Results of assessment are provided and show different accuracy according to the statistical distribution of data.

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Biblioteca Digital Brasileira de Computação - Contato:
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