Creator:

Bodyanskiy, Yevgeniy V. ; Tyshchenko, Oleksii K.

Contributor:

Kulczycki, Piotr - ed. ; Kacprzyk, Janusz - ed. ; Kóczy, László T. - ed. ; Mesiar, Radko - ed.

Title:

A hybrid cascade neuro-fuzzy network with pools of extended neo-fuzzy neurons and its deep learning

Subtitle:

.

Group publication title:

AMCS, volume 29 (2019)

Subject and Keywords:

data streaming ; membership function ; training procedure ; adaptive neuro-fuzzy system ; extended neo-fuzzy neuron

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2019

Resource Type:

artykuł

DOI:

10.2478/amcs-2019-0035

Pages:

477-488

Source:

AMCS, volume 29, number 3 (2019) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego