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

Result code in 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>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

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

Original language description

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.

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

AH - Economics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2009

Confidentiality

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

Name of the periodical

Acta Polytechnica

ISSN

1210-2709

e-ISSN

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Volume of the periodical

49

Issue of the periodical within the volume

2-3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

5

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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