Neural networks’ learning process acceleration

Neural networks’ learning process acceleration

This study is devoted to evaluating the process of training of a parallel system in the form of an artificial neural network, which is built using a genetic algorithm. The methods that allow to achieve this goal are computer simulation of a neural network on multi-core CPUs and a genetic algorithm f...

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Bibliographic Details
Date:2020
Main Authors: Katerynych, L., Veres, M.M., Safarov, E.
Format: Article
Language:English
Published: PROBLEMS IN PROGRAMMING 2020
Subjects:
multi-core CPUs
artificial neural networks
artificial neuron
genetic algorithm
selection
crossing
mutation
parallel computing
UDC 004.4
Online Access:https://pp.isofts.kiev.ua/index.php/ojs1/article/view/423
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Journal Title:Problems in programming
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Problems in programming
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Summary:This study is devoted to evaluating the process of training of a parallel system in the form of an artificial neural network, which is built using a genetic algorithm. The methods that allow to achieve this goal are computer simulation of a neural network on multi-core CPUs and a genetic algorithm for finding the weights of an artificial neural network. The performance of sequential and parallel training processes of artificial neural network is compared.Problems in programming 2020; 2-3: 313-321

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