1. bookTom 31 (2021): Zeszyt 4 (December 2021)
    Advanced Machine Learning Techniques in Data Analysis (special section, pp. 549-611), Maciej Kusy, Rafał Scherer, and Adam Krzyżak (Eds.)
Informacje o czasopiśmie
License
Format
Czasopismo
eISSN
2083-8492
Pierwsze wydanie
05 Apr 2007
Częstotliwość wydawania
4 razy w roku
Języki
Angielski
access type Otwarty dostęp

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

Data publikacji: 30 Dec 2021
Tom & Zeszyt: Tom 31 (2021) - Zeszyt 4 (December 2021)<br/>Advanced Machine Learning Techniques in Data Analysis (special section, pp. 549-611), Maciej Kusy, Rafał Scherer, and Adam Krzyżak (Eds.)
Zakres stron: 577 - 586
Otrzymano: 28 Apr 2021
Przyjęty: 07 Sep 2021
Informacje o czasopiśmie
License
Format
Czasopismo
eISSN
2083-8492
Pierwsze wydanie
05 Apr 2007
Częstotliwość wydawania
4 razy w roku
Języki
Angielski
Abstract

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.

Keywords

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