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2 International Journal of Applied Mathematics and Computer Science

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A modified particle swarm optimization procedure for triggering fuzzy flip-flop neural networks

Kowalski Piotr A., Słoczyński Tomasz

International Journal of Applied Mathematics and Computer Science

2021

Vol. 31, no. 4

577--586

The aim of the presented study is to investigate the application of an optimization algorithm based on swarm intelligence to the configuration of a fuzzy flip-flop neural network. Research on solving this problem consists of the following stages. The first one is to analyze the impact of the basic internal parameters of the neural network and the particle swarm optimization (PSO) algorithm. Subsequently, some modifications to the PSO algorithm are investigated. Approximations of trigonometric functions are then adopted as the main task to be performed by the neural network. As a result of the numerical verification of the problem, a set of rules are developed that can be helpful in constructing a fuzzy flip-flop type neural network. The obtained results of the computations significantly simplify the structure of the neural network in relation to similar conditions known from the literature.

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

Bodyanskiy Yevgeniy V., Tyshchenko Oleksii K.

International Journal of Applied Mathematics and Computer Science

2019

Vol. 29, no. 3

477--488

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.