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Paper details
Number 3 - September 2019
Volume 29 - 2019
A hybrid cascade neuro-fuzzy network with pools of extended neo-fuzzy neurons and its deep learning
Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko
Abstract
This research contribution instantiates a framework of a hybrid cascade neural network based on the application of a
specific sort of neo-fuzzy elements and a new peculiar adaptive training rule. The main trait of the offered system is its
competence to continue intensifying its cascades until the required accuracy is gained. A distinctive rapid training procedure
is also covered for this case that offers the possibility to operate with non-stationary data streams in an attempt to provide
online training of multiple parametric variables. A new training criterion is examined for handling non-stationary objects.
Additionally, there is always an occasion to set up (increase) the inference order and the number of membership relations
inside the extended neo-fuzzy neuron.
Keywords
data stream, membership function, training procedure, adaptive neuro-fuzzy system, extended neo-fuzzy neuron