Prediction of Network Traffic by Elman Neural Network

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU108899" target="_blank" >RIV/00216305:26220/14:PU108899 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Prediction of Network Traffic by Elman Neural Network

Original language description

This article deals with the prediction of network traffic by the Elman neural network. The reader finds the results of experimental tests of prediction of network traffic here. The testing of prediction of network traffic was realized on the network traffic, which was caught in the local network. The accuracy of prediction of network traffic by the Elman neural network was tested with use of several types of topology of the Elman neural network. The article describes the solution of System for dynamic allocation of bandwidth. The system is based on the prediction of network traffic by the Elman neural network. The proposed system effectively allocates available bandwidh of output of router between the queues of port.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JA - Electronics and optoelectronics

OECD FORD branch

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Project

<a href="/en/project/ED2.1.00%2F03.0072" target="_blank" >ED2.1.00/03.0072: Centre of sensor, information and communication systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2014

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Elektrorevue - Internetový časopis (http://www.elektrorevue.cz)

ISSN

1213-1539

e-ISSN

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Volume of the periodical

15

Issue of the periodical within the volume

3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

7

Pages from-to

1-7

UT code for WoS article

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EID of the result in the Scopus database

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