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Нечітка ітераційна метаідентифікація штучних нейросіток в мультиагентному середовищі

Authors: Jampolskiy, L. S.;

Нечітка ітераційна метаідентифікація штучних нейросіток в мультиагентному середовищі

Abstract

На основі розробленого реляційного класифікатора запропонований універсальний підхід довибору задовольняючої топології нейросіток, яка відповідає вимогам модельованої прикладної задачі. Реалізація підходу базується на використанні гнучкої інтелектуалізованої мультиагентної системи з багатоцільовою конфігурацією її складових з функціями метаідентифікації. Розкрита взаємодія компонент системи в процесі їх функціонування. The main purpose of an article consists in а development of the new artificial neuron network’s topology determination methodology. The universal approach of the NeuroNets’ satisfactory topology automated choice, which corresponds to the demands of the modeling applied problem (or task), is proposed. The approach’s realization based on using of the flexible automated multiagent system with multiobject configuration of its components with the metaidentification’s functions. The peculiarities of the system’s components interaction in its function are uncovered.

Keywords

topology, експертна система, рейтингове оцінювання, сітка Петрі, топологія нейросітки, metaidentification, чисельні процедури, нечітка метаідентифікація, продукційні правила, fuzzy controller, агентно-орієнтована підсистема, neuron network, multiagent environment, гнучка інтелектуалізована мультиагентна конфігурація, набір вирішальних класифікаційних ознак, агенти/мультиагенти з функціями метаідентифікації, штучна нейросітка, фаззі-контролер, логічна модель поетапного синтезу

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green