Demand Modelling in Telecommunications, Comparison of Statistical methods and Approaches based upon Artifical Intelligence Methods including Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00158016" target="_blank" >RIV/68407700:21230/09:00158016 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Demand Modelling in Telecommunications, Comparison of Statistical methods and Approaches based upon Artifical Intelligence Methods including Neural Networks

Popis výsledku v původním jazyce

This article is focused on analysis of the existing possibilities of Standard Statistical Methods and Artificial Intelligence Methods utilization for a short-term forecast and simulation of Demand in the field of Telecommunications. The most wide-spreadare methods based upon the Time Series Analysis. Nowdays the approaches grounded upon the Artificial Intelligence Methods including Neural Networks are being dynamically booming. The separate approaches will be used within the research study for the Demand modelling in Telecommunications and the results of these models will be compared with actual guaranteed values. Then will be examined the Neural Networks utilization with respect to a model quality.

Název v anglickém jazyce

Demand Modelling in Telecommunications, Comparison of Statistical methods and Approaches based upon Artifical Intelligence Methods including Neural Networks

Popis výsledku anglicky

This article is focused on analysis of the existing possibilities of Standard Statistical Methods and Artificial Intelligence Methods utilization for a short-term forecast and simulation of Demand in the field of Telecommunications. The most wide-spreadare methods based upon the Time Series Analysis. Nowdays the approaches grounded upon the Artificial Intelligence Methods including Neural Networks are being dynamically booming. The separate approaches will be used within the research study for the Demand modelling in Telecommunications and the results of these models will be compared with actual guaranteed values. Then will be examined the Neural Networks utilization with respect to a model quality.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název periodika

Acta Polytechnica

ISSN

1210-2709

e-ISSN

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Svazek periodika

49

Číslo periodika v rámci svazku

2-3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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